04054nas a2201033 4500008004100000022001400041245007700055210006900132260001300201300001100214490000700225520114900232653001901381653001401400653001901414653002201433653001701455653002001472653001801492653003401510653001101544653001701555653001401572653003601586653002801622100002201650700001901672700002601691700002001717700002101737700002201758700002001780700001901800700002201819700001901841700002101860700001901881700001601900700002001916700001801936700002101954700002601975700002202001700002102023700002202044700002002066700001802086700002102104700002002125700002402145700001702169700002202186700002102208700002202229700001902251700002602270700002302296700001602319700002502335700002502360700001802385700001902403700002802422700002302450700002202473700002502495700001902520700002302539700002402562700002002586700002302606700002002629700002002649700002002669700002202689700002402711700002302735700002002758700002002778700002602798700002402824700003002848700003002878700001702908700001802925700002202943700001902965856003602984 2009 eng d a1546-171800aMultiple loci influence erythrocyte phenotypes in the CHARGE Consortium.0 aMultiple loci influence erythrocyte phenotypes in the CHARGE Con c2009 Nov a1191-80 v413 a
Measurements of erythrocytes within the blood are important clinical traits and can indicate various hematological disorders. We report here genome-wide association studies (GWAS) for six erythrocyte traits, including hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and red blood cell count (RBC). We performed an initial GWAS in cohorts of the CHARGE Consortium totaling 24,167 individuals of European ancestry and replication in additional independent cohorts of the HaemGen Consortium totaling 9,456 individuals. We identified 23 loci significantly associated with these traits in a meta-analysis of the discovery and replication cohorts (combined P values ranging from 5 x 10(-8) to 7 x 10(-86)). Our findings include loci previously associated with these traits (HBS1L-MYB, HFE, TMPRSS6, TFR2, SPTA1) as well as new associations (EPO, TFRC, SH2B3 and 15 other loci). This study has identified new determinants of erythrocyte traits, offering insight into common variants underlying variation in erythrocyte measures.
10aBlood Pressure10aCell Line10aCohort Studies10aEndothelial Cells10aErythrocytes10aGene Expression10aGenome, Human10aGenome-Wide Association Study10aHumans10aHypertension10aPhenotype10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci1 aGanesh, Santhi, K1 aZakai, Neil, A1 avan Rooij, Frank, J A1 aSoranzo, Nicole1 aSmith, Albert, V1 aNalls, Michael, A1 aChen, Ming-Huei1 aKöttgen, Anna1 aGlazer, Nicole, L1 aDehghan, Abbas1 aKuhnel, Brigitte1 aAspelund, Thor1 aYang, Qiong1 aTanaka, Toshiko1 aJaffe, Andrew1 aBis, Joshua, C M1 aVerwoert, Germaine, C1 aTeumer, Alexander1 aFox, Caroline, S1 aGuralnik, Jack, M1 aEhret, Georg, B1 aRice, Kenneth1 aFelix, Janine, F1 aRendon, Augusto1 aEiriksdottir, Gudny1 aLevy, Daniel1 aPatel, Kushang, V1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aHofman, Albert1 aSambrook, Jennifer, G1 aHernandez, Dena, G1 aZheng, Gang1 aBandinelli, Stefania1 aSingleton, Andrew, B1 aCoresh, Josef1 aLumley, Thomas1 aUitterlinden, André, G1 aVangils, Janine, M1 aLauner, Lenore, J1 aCupples, Adrienne, L1 aOostra, Ben, A1 aZwaginga, Jaap-Jan1 aOuwehand, Willem, H1 aThein, Swee-Lay1 aMeisinger, Christa1 aDeloukas, Panos1 aNauck, Matthias1 aSpector, Tim, D1 aGieger, Christian1 aGudnason, Vilmundur1 aDuijn, Cornelia, M1 aPsaty, Bruce, M1 aFerrucci, Luigi1 aChakravarti, Aravinda1 aGreinacher, Andreas1 aO'Donnell, Christopher, J1 aWitteman, Jacqueline, C M1 aFurth, Susan1 aCushman, Mary1 aHarris, Tamara, B1 aLin, Jing-Ping uhttps://chs-nhlbi.org/node/114104323nas a2201033 4500008004100000022001400041245011200055210006900167260001300236300001300249490000600262520134000268653000901608653002001617653001901637653004001656653001101696653003801707653003401745653001101779653000901790653001601799653002601815653001201841653003601853653002401889100002601913700002501939700001901964700001901983700002202002700001202024700002302036700002102059700001902080700002402099700002002123700002202143700002102165700002502186700002402211700002302235700002602258700002102284700001902305700002302324700002102347700002102368700002202389700002202411700002202433700002002455700002202475700001602497700002002513700002002533700002202553700002602575700001602601700002302617700002202640700001602662700001602678700002502694700001902719700002102738700001902759700002402778700002402802700003002826700002702856700002202883700002402905700001902929700001902948700002602967700002802993700003003021700001903051700002203070700002403092700002603116700002303142700002303165700002503188700002103213700001903234856003603253 2009 eng d a1553-740400aNRXN3 is a novel locus for waist circumference: a genome-wide association study from the CHARGE Consortium.0 aNRXN3 is a novel locus for waist circumference a genomewide asso c2009 Jun ae10005390 v53 aCentral abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.
10aAged10aBody Mass Index10aCohort Studies10aEuropean Continental Ancestry Group10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aNerve Tissue Proteins10aObesity10aPolymorphism, Single Nucleotide10aWaist Circumference1 aHeard-Costa, Nancy, L1 aZillikens, Carola, M1 aMonda, Keri, L1 aJohansson, Asa1 aHarris, Tamara, B1 aFu, Mao1 aHaritunians, Talin1 aFeitosa, Mary, F1 aAspelund, Thor1 aEiriksdottir, Gudny1 aGarcia, Melissa1 aLauner, Lenore, J1 aSmith, Albert, V1 aMitchell, Braxton, D1 aMcArdle, Patrick, F1 aShuldiner, Alan, R1 aBielinski, Suzette, J1 aBoerwinkle, Eric1 aBrancati, Fred1 aDemerath, Ellen, W1 aPankow, James, S1 aArnold, Alice, M1 aChen, Yii-Der Ida1 aGlazer, Nicole, L1 aMcKnight, Barbara1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aAmin, Najaf1 aCampbell, Harry1 aGyllensten, Ulf1 aPattaro, Cristian1 aPramstaller, Peter, P1 aRudan, Igor1 aStruchalin, Maksim1 aVitart, Veronique1 aGao, Xiaoyi1 aKraja, Aldi1 aProvince, Michael, A1 aZhang, Qunyuan1 aAtwood, Larry, D1 aDupuis, Josée1 aHirschhorn, Joel, N1 aJaquish, Cashell, E1 aO'Donnell, Christopher, J1 aVasan, Ramachandran, S1 aWhite, Charles, C1 aAulchenko, Yurii, S1 aEstrada, Karol1 aHofman, Albert1 aRivadeneira, Fernando1 aUitterlinden, André, G1 aWitteman, Jacqueline, C M1 aOostra, Ben, A1 aKaplan, Robert, C1 aGudnason, Vilmundur1 aO'Connell, Jeffrey, R1 aBorecki, Ingrid, B1 aDuijn, Cornelia, M1 aCupples, Adrienne, L1 aFox, Caroline, S1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/110714196nas a2204789 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2010 eng d a1546-171800aAssociation analyses of 249,796 individuals reveal 18 new loci associated with body mass index.0 aAssociation analyses of 249796 individuals reveal 18 new loci as c2010 Nov a937-480 v423 aObesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
10aBody Height10aBody Mass Index10aBody Size10aBody Weight10aChromosome Mapping10aEuropean Continental Ancestry Group10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aObesity10aPolymorphism, Single Nucleotide1 aSpeliotes, Elizabeth, K1 aWiller, Cristen, J1 aBerndt, Sonja, I1 aMonda, Keri, L1 aThorleifsson, Gudmar1 aJackson, Anne, U1 aAllen, Hana, Lango1 aLindgren, Cecilia, M1 aLuan, Jian'an1 aMägi, Reedik1 aRandall, Joshua, C1 aVedantam, Sailaja1 aWinkler, Thomas, W1 aQi, Lu1 aWorkalemahu, Tsegaselassie1 aHeid, Iris, M1 aSteinthorsdottir, Valgerdur1 aStringham, Heather, M1 aWeedon, Michael, N1 aWheeler, Eleanor1 aWood, Andrew, R1 aFerreira, Teresa1 aWeyant, Robert, J1 aSegrè, Ayellet, V1 aEstrada, Karol1 aLiang, Liming1 aNemesh, James1 aPark, Ju-Hyun1 aGustafsson, Stefan1 aKilpeläinen, Tuomas, O1 aYang, Jian1 aBouatia-Naji, Nabila1 aEsko, Tõnu1 aFeitosa, Mary, F1 aKutalik, Zoltán1 aMangino, Massimo1 aRaychaudhuri, Soumya1 aScherag, Andre1 aSmith, Albert, Vernon1 aWelch, Ryan1 aZhao, Jing Hua1 aAben, Katja, K1 aAbsher, Devin, M1 aAmin, Najaf1 aDixon, Anna, L1 aFisher, Eva1 aGlazer, Nicole, L1 aGoddard, Michael, E1 aHeard-Costa, Nancy, L1 aHoesel, Volker1 aHottenga, Jouke-Jan1 aJohansson, Asa1 aJohnson, Toby1 aKetkar, Shamika1 aLamina, Claudia1 aLi, Shengxu1 aMoffatt, Miriam, F1 aMyers, Richard, H1 aNarisu, Narisu1 aPerry, John, R B1 aPeters, Marjolein, J1 aPreuss, Michael1 aRipatti, Samuli1 aRivadeneira, Fernando1 aSandholt, Camilla1 aScott, Laura, J1 aTimpson, Nicholas, J1 aTyrer, Jonathan, P1 avan Wingerden, Sophie1 aWatanabe, Richard, M1 aWhite, Charles, C1 aWiklund, Fredrik1 aBarlassina, Christina1 aChasman, Daniel, I1 aCooper, Matthew, N1 aJansson, John-Olov1 aLawrence, Robert, W1 aPellikka, Niina1 aProkopenko, Inga1 aShi, Jianxin1 aThiering, Elisabeth1 aAlavere, Helene1 aAlibrandi, Maria, T S1 aAlmgren, Peter1 aArnold, Alice, M1 aAspelund, Thor1 aAtwood, Larry, D1 aBalkau, Beverley1 aBalmforth, Anthony, J1 aBennett, Amanda, J1 aBen-Shlomo, Yoav1 aBergman, Richard, N1 aBergmann, Sven1 aBiebermann, Heike1 aBlakemore, Alexandra, I F1 aBoes, Tanja1 aBonnycastle, Lori, L1 aBornstein, Stefan, R1 aBrown, Morris, J1 aBuchanan, Thomas, A1 aBusonero, Fabio1 aCampbell, Harry1 aCappuccio, Francesco, P1 aCavalcanti-Proença, Christine1 aChen, Yii-Der Ida1 aChen, Chih-Mei1 aChines, Peter, S1 aClarke, Robert1 aCoin, Lachlan1 aConnell, John1 aDay, Ian, N M1 aHeijer, Martin, den1 aDuan, Jubao1 aEbrahim, Shah1 aElliott, Paul1 aElosua, Roberto1 aEiriksdottir, Gudny1 aErdos, Michael, R1 aEriksson, Johan, G1 aFacheris, Maurizio, F1 aFelix, Stephan, B1 aFischer-Posovszky, Pamela1 aFolsom, Aaron, R1 aFriedrich, Nele1 aFreimer, Nelson, B1 aFu, Mao1 aGaget, Stefan1 aGejman, Pablo, V1 aGeus, Eco, J C1 aGieger, Christian1 aGjesing, Anette, P1 aGoel, Anuj1 aGoyette, Philippe1 aGrallert, Harald1 aGrässler, Jürgen1 aGreenawalt, Danielle, M1 aGroves, Christopher, J1 aGudnason, Vilmundur1 aGuiducci, Candace1 aHartikainen, Anna-Liisa1 aHassanali, Neelam1 aHall, Alistair, S1 aHavulinna, Aki, S1 aHayward, Caroline1 aHeath, Andrew, C1 aHengstenberg, Christian1 aHicks, Andrew, A1 aHinney, Anke1 aHofman, Albert1 aHomuth, Georg1 aHui, Jennie1 aIgl, Wilmar1 aIribarren, Carlos1 aIsomaa, Bo1 aJacobs, Kevin, B1 aJarick, Ivonne1 aJewell, Elizabeth1 aJohn, Ulrich1 aJørgensen, Torben1 aJousilahti, Pekka1 aJula, Antti1 aKaakinen, Marika1 aKajantie, Eero1 aKaplan, Lee, M1 aKathiresan, Sekar1 aKettunen, Johannes1 aKinnunen, Leena1 aKnowles, Joshua, W1 aKolcic, Ivana1 aKönig, Inke, R1 aKoskinen, Seppo1 aKovacs, Peter1 aKuusisto, Johanna1 aKraft, Peter1 aKvaløy, Kirsti1 aLaitinen, Jaana1 aLantieri, Olivier1 aLanzani, Chiara1 aLauner, Lenore, J1 aLecoeur, Cécile1 aLehtimäki, Terho1 aLettre, Guillaume1 aLiu, Jianjun1 aLokki, Marja-Liisa1 aLorentzon, Mattias1 aLuben, Robert, N1 aLudwig, Barbara1 aManunta, Paolo1 aMarek, Diana1 aMarre, Michel1 aMartin, Nicholas, G1 aMcArdle, Wendy, L1 aMcCarthy, Anne1 aMcKnight, Barbara1 aMeitinger, Thomas1 aMelander, Olle1 aMeyre, David1 aMidthjell, Kristian1 aMontgomery, Grant, W1 aMorken, Mario, A1 aMorris, Andrew, P1 aMulic, Rosanda1 aNgwa, Julius, S1 aNelis, Mari1 aNeville, Matt, J1 aNyholt, Dale, R1 aO'Donnell, Christopher, J1 aO'Rahilly, Stephen1 aOng, Ken, K1 aOostra, Ben1 aParé, Guillaume1 aParker, Alex, N1 aPerola, Markus1 aPichler, Irene1 aPietiläinen, Kirsi, H1 aPlatou, Carl, G P1 aPolasek, Ozren1 aPouta, Anneli1 aRafelt, Suzanne1 aRaitakari, Olli1 aRayner, Nigel, W1 aRidderstråle, Martin1 aRief, Winfried1 aRuokonen, Aimo1 aRobertson, Neil, R1 aRzehak, Peter1 aSalomaa, Veikko1 aSanders, Alan, R1 aSandhu, Manjinder, S1 aSanna, Serena1 aSaramies, Jouko1 aSavolainen, Markku, J1 aScherag, Susann1 aSchipf, Sabine1 aSchreiber, Stefan1 aSchunkert, Heribert1 aSilander, Kaisa1 aSinisalo, Juha1 aSiscovick, David, S1 aSmit, Jan, H1 aSoranzo, Nicole1 aSovio, Ulla1 aStephens, Jonathan1 aSurakka, Ida1 aSwift, Amy, J1 aTammesoo, Mari-Liis1 aTardif, Jean-Claude1 aTeder-Laving, Maris1 aTeslovich, Tanya, M1 aThompson, John, R1 aThomson, Brian1 aTönjes, Anke1 aTuomi, Tiinamaija1 avan Meurs, Joyce, B J1 avan Ommen, Gert-Jan1 aVatin, Vincent1 aViikari, Jorma1 aVisvikis-Siest, Sophie1 aVitart, Veronique1 aVogel, Carla, I G1 aVoight, Benjamin, F1 aWaite, Lindsay, L1 aWallaschofski, Henri1 aWalters, Bragi, G1 aWiden, Elisabeth1 aWiegand, Susanna1 aWild, Sarah, H1 aWillemsen, Gonneke1 aWitte, Daniel, R1 aWitteman, Jacqueline, C1 aXu, Jianfeng1 aZhang, Qunyuan1 aZgaga, Lina1 aZiegler, Andreas1 aZitting, Paavo1 aBeilby, John, P1 aFarooqi, Sadaf1 aHebebrand, Johannes1 aHuikuri, Heikki, V1 aJames, Alan, L1 aKähönen, Mika1 aLevinson, Douglas, F1 aMacciardi, Fabio1 aNieminen, Markku, S1 aOhlsson, Claes1 aPalmer, Lyle, J1 aRidker, Paul, M1 aStumvoll, Michael1 aBeckmann, Jacques, S1 aBoeing, Heiner1 aBoerwinkle, Eric1 aBoomsma, Dorret, I1 aCaulfield, Mark, J1 aChanock, Stephen, J1 aCollins, Francis, S1 aCupples, Adrienne, L1 aSmith, George Davey1 aErdmann, Jeanette1 aFroguel, Philippe1 aGrönberg, Henrik1 aGyllensten, Ulf1 aHall, Per1 aHansen, Torben1 aHarris, Tamara, B1 aHattersley, Andrew, T1 aHayes, Richard, B1 aHeinrich, Joachim1 aHu, Frank, B1 aHveem, Kristian1 aIllig, Thomas1 aJarvelin, Marjo-Riitta1 aKaprio, Jaakko1 aKarpe, Fredrik1 aKhaw, Kay-Tee1 aKiemeney, Lambertus, A1 aKrude, Heiko1 aLaakso, Markku1 aLawlor, Debbie, A1 aMetspalu, Andres1 aMunroe, Patricia, B1 aOuwehand, Willem, H1 aPedersen, Oluf1 aPenninx, Brenda, W1 aPeters, Annette1 aPramstaller, Peter, P1 aQuertermous, Thomas1 aReinehr, Thomas1 aRissanen, Aila1 aRudan, Igor1 aSamani, Nilesh, J1 aSchwarz, Peter, E H1 aShuldiner, Alan, R1 aSpector, Timothy, D1 aTuomilehto, Jaakko1 aUda, Manuela1 aUitterlinden, Andre1 aValle, Timo, T1 aWabitsch, Martin1 aWaeber, Gérard1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWilson, James, F1 aWright, Alan, F1 aZillikens, Carola, M1 aChatterjee, Nilanjan1 aMcCarroll, Steven, A1 aPurcell, Shaun1 aSchadt, Eric, E1 aVisscher, Peter, M1 aAssimes, Themistocles, L1 aBorecki, Ingrid, B1 aDeloukas, Panos1 aFox, Caroline, S1 aGroop, Leif, C1 aHaritunians, Talin1 aHunter, David, J1 aKaplan, Robert, C1 aMohlke, Karen, L1 aO'Connell, Jeffrey, R1 aPeltonen, Leena1 aSchlessinger, David1 aStrachan, David, P1 aDuijn, Cornelia, M1 aWichmann, H-Erich1 aFrayling, Timothy, M1 aThorsteinsdottir, Unnur1 aAbecasis, Goncalo, R1 aBarroso, Inês1 aBoehnke, Michael1 aStefansson, Kari1 aNorth, Kari, E1 aMcCarthy, Mark, I1 aHirschhorn, Joel, N1 aIngelsson, Erik1 aLoos, Ruth, J F1 aMAGIC1 aProcardis Consortium uhttps://chs-nhlbi.org/node/123704239nas a2200781 4500008004100000022001400041245024400055210006900299260001300368300001100381490000600392520185900398653002202257653000902279653002202288653001902310653001902329653004002348653001102388653003402399653001802433653001102451653001402462653000902476653001602485653003602501653000902537653003302546100002302579700002102602700002402623700002302647700002202670700002002692700002502712700001902737700001902756700002302775700001902798700002602817700001902843700002102862700002102883700002402904700002302928700001802951700002102969700001802990700002303008700002403031700002303055700002003078700002103098700001903119700002303138700001803161700003003179700002803209700002203237700002403259700001703283700002303300700002003323700003003343700002103373700002703394856003603421 2010 eng d a1942-326800aAssociation of genome-wide variation with the risk of incident heart failure in adults of European and African ancestry: a prospective meta-analysis from the cohorts for heart and aging research in genomic epidemiology (CHARGE) consortium.0 aAssociation of genomewide variation with the risk of incident he c2010 Jun a256-660 v33 aBACKGROUND: Although genetic factors contribute to the onset of heart failure (HF), no large-scale genome-wide investigation of HF risk has been published to date. We have investigated the association of 2,478,304 single-nucleotide polymorphisms with incident HF by meta-analyzing data from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.
METHODS AND RESULTS: Eligible participants for these analyses were of European or African ancestry and free of clinical HF at baseline. Each study independently conducted genome-wide scans and imputed data to the approximately 2.5 million single-nucleotide polymorphisms in HapMap. Within each study, Cox proportional hazards regression models provided age- and sex-adjusted estimates of the association between each variant and time to incident HF. Fixed-effect meta-analyses combined results for each single-nucleotide polymorphism from the 4 cohorts to produce an overall association estimate and P value. A genome-wide significance P value threshold was set a priori at 5.0x10(-7). During a mean follow-up of 11.5 years, 2526 incident HF events (12%) occurred in 20 926 European-ancestry participants. The meta-analysis identified a genome-wide significant locus at chromosomal position 15q22 (1.4x10(-8)), which was 58.8 kb from USP3. Among 2895 African-ancestry participants, 466 incident HF events (16%) occurred during a mean follow-up of 13.7 years. One genome-wide significant locus was identified at 12q14 (6.7x10(-8)), which was 6.3 kb from LRIG3.
CONCLUSIONS: We identified 2 loci that were associated with incident HF and exceeded genome-wide significance. The findings merit replication in other community-based settings of incident HF.
10aAfrican Americans10aAged10aAged, 80 and over10aCohort Studies10aEndopeptidases10aEuropean Continental Ancestry Group10aFemale10aGenome-Wide Association Study10aHeart Failure10aHumans10aIncidence10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aRisk10aUbiquitin-Specific Proteases1 aSmith, Nicholas, L1 aFelix, Janine, F1 aMorrison, Alanna, C1 aDemissie, Serkalem1 aGlazer, Nicole, L1 aLoehr, Laura, R1 aCupples, Adrienne, L1 aDehghan, Abbas1 aLumley, Thomas1 aRosamond, Wayne, D1 aLieb, Wolfgang1 aRivadeneira, Fernando1 aBis, Joshua, C1 aFolsom, Aaron, R1 aBenjamin, Emelia1 aAulchenko, Yurii, S1 aHaritunians, Talin1 aCouper, David1 aMurabito, Joanne1 aWang, Ying, A1 aStricker, Bruno, H1 aGottdiener, John, S1 aChang, Patricia, P1 aWang, Thomas, J1 aRice, Kenneth, M1 aHofman, Albert1 aHeckbert, Susan, R1 aFox, Ervin, R1 aO'Donnell, Christopher, J1 aUitterlinden, André, G1 aRotter, Jerome, I1 aWillerson, James, T1 aLevy, Daniel1 aDuijn, Cornelia, M1 aPsaty, Bruce, M1 aWitteman, Jacqueline, C M1 aBoerwinkle, Eric1 aVasan, Ramachandran, S uhttps://chs-nhlbi.org/node/119709616nas a2202929 4500008004100000022001400041245007900055210006900134260001600203300001100219490000800230520140900238653002201647653001201669653003701681653002101718653002101739653002801760653001101788653004001799653001101839653001701850653003401867653001301901653001101914653002101925653001101946653001001957653000901967653000901976653003901985653001402024653003602038653002602074653003102100653001802131100002402149700002002173700002102193700002502214700002602239700002102265700002602286700002002312700002302332700002302355700002902378700002402407700001802431700002002449700001902469700002302488700001902511700002402530700002502554700002102579700001902600700002502619700001902644700001802663700001602681700001702697700001602714700002002730700001702750700002002767700002002787700001802807700001602825700001702841700002402858700003002882700002102912700002102933700001802954700002002972700001402992700001803006700002003024700002103044700001803065700002103083700002003104700003003124700002103154700002303175700002203198700002303220700002403243700002503267700002003292700002403312700002403336700002203360700002803382700001703410700002303427700002203450700002003472700001703492700002603509700002003535700002003555700002203575700001903597700002003616700002503636700002003661700001703681700002403698700001803722700002003740700002003760700002003780700001903800700001603819700001903835700002003854700001703874700002003891700002603911700001903937700001903956700002703975700002304002700002204025700002004047700002104067700001904088700003004107700002404137700002604161700002504187700002204212700002004234700002204254700001904276700001804295700002404313700001904337700002104356700002704377700001704404700001804421700002004439700002304459700002204482700002404504700002204528700002304550700002104573700002204594700002404616700002004640700001804660700001904678700001904697700001904716700002704735700002604762700002004788700001604808700001804824700002404842700001904866700002104885700002804906700001804934700002204952700002204974700002404996700002205020700002305042700002205065700002005087700002205107700001905129700002005148700002205168700002305190700002005213700002205233700001805255700002205273700002005295700002405315700002305339700002505362700001905387700001805406700002205424700002405446700002105470700002305491700002005514700001905534700002505553700002305578700002405601700002405625700001905649700002505668700002805693700002905721700002405750700002105774700002005795700001805815700001805833700002105851700002705872700002005899700002205919700002305941700002305964700002105987700001606008700002806024700002406052700002206076700002106098700002106119700002406140700002206164700001806186700002206204700002506226700002006251700002206271700002106293700002306314700002006337700002106357700002406378700002206402700002406424700002506448700002506473700002006498700002106518700002306539700002006562700002506582700002106607700002206628856003606650 2010 eng d a1476-468700aBiological, clinical and population relevance of 95 loci for blood lipids.0 aBiological clinical and population relevance of 95 loci for bloo c2010 Aug 05 a707-130 v4663 aPlasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
10aAfrican Americans10aAnimals10aAsian Continental Ancestry Group10aCholesterol, HDL10aCholesterol, LDL10aCoronary Artery Disease10aEurope10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenome-Wide Association Study10aGenotype10aHumans10aLipid Metabolism10aLipids10aLiver10aMale10aMice10aN-Acetylgalactosaminyltransferases10aPhenotype10aPolymorphism, Single Nucleotide10aProtein Phosphatase 110aReproducibility of Results10aTriglycerides1 aTeslovich, Tanya, M1 aMusunuru, Kiran1 aSmith, Albert, V1 aEdmondson, Andrew, C1 aStylianou, Ioannis, M1 aKoseki, Masahiro1 aPirruccello, James, P1 aRipatti, Samuli1 aChasman, Daniel, I1 aWiller, Cristen, J1 aJohansen, Christopher, T1 aFouchier, Sigrid, W1 aIsaacs, Aaron1 aPeloso, Gina, M1 aBarbalic, Maja1 aRicketts, Sally, L1 aBis, Joshua, C1 aAulchenko, Yurii, S1 aThorleifsson, Gudmar1 aFeitosa, Mary, F1 aChambers, John1 aOrho-Melander, Marju1 aMelander, Olle1 aJohnson, Toby1 aLi, Xiaohui1 aGuo, Xiuqing1 aLi, Mingyao1 aCho, Yoon, Shin1 aGo, Min, Jin1 aKim, Young, Jin1 aLee, Jong-Young1 aPark, Taesung1 aKim, Kyunga1 aSim, Xueling1 aOng, Rick, Twee-Hee1 aCroteau-Chonka, Damien, C1 aLange, Leslie, A1 aSmith, Joshua, D1 aSong, Kijoung1 aZhao, Jing, Hua1 aYuan, Xin1 aLuan, Jian'an1 aLamina, Claudia1 aZiegler, Andreas1 aZhang, Weihua1 aZee, Robert, Y L1 aWright, Alan, F1 aWitteman, Jacqueline, C M1 aWilson, James, F1 aWillemsen, Gonneke1 aWichmann, H-Erich1 aWhitfield, John, B1 aWaterworth, Dawn, M1 aWareham, Nicholas, J1 aWaeber, Gérard1 aVollenweider, Peter1 aVoight, Benjamin, F1 aVitart, Veronique1 aUitterlinden, André, G1 aUda, Manuela1 aTuomilehto, Jaakko1 aThompson, John, R1 aTanaka, Toshiko1 aSurakka, Ida1 aStringham, Heather, M1 aSpector, Tim, D1 aSoranzo, Nicole1 aSmit, Johannes, H1 aSinisalo, Juha1 aSilander, Kaisa1 aSijbrands, Eric, J G1 aScuteri, Angelo1 aScott, James1 aSchlessinger, David1 aSanna, Serena1 aSalomaa, Veikko1 aSaharinen, Juha1 aSabatti, Chiara1 aRuokonen, Aimo1 aRudan, Igor1 aRose, Lynda, M1 aRoberts, Robert1 aRieder, Mark1 aPsaty, Bruce, M1 aPramstaller, Peter, P1 aPichler, Irene1 aPerola, Markus1 aPenninx, Brenda, W J H1 aPedersen, Nancy, L1 aPattaro, Cristian1 aParker, Alex, N1 aParé, Guillaume1 aOostra, Ben, A1 aO'Donnell, Christopher, J1 aNieminen, Markku, S1 aNickerson, Deborah, A1 aMontgomery, Grant, W1 aMeitinger, Thomas1 aMcPherson, Ruth1 aMcCarthy, Mark, I1 aMcArdle, Wendy1 aMasson, David1 aMartin, Nicholas, G1 aMarroni, Fabio1 aMangino, Massimo1 aMagnusson, Patrik, K E1 aLucas, Gavin1 aLuben, Robert1 aLoos, Ruth, J F1 aLokki, Marja-Liisa1 aLettre, Guillaume1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLakatta, Edward, G1 aLaaksonen, Reijo1 aKyvik, Kirsten, O1 aKronenberg, Florian1 aKönig, Inke, R1 aKhaw, Kay-Tee1 aKaprio, Jaakko1 aKaplan, Lee, M1 aJohansson, Asa1 aJarvelin, Marjo-Riitta1 aJanssens, Cecile, J W1 aIngelsson, Erik1 aIgl, Wilmar1 aHovingh, Kees1 aHottenga, Jouke-Jan1 aHofman, Albert1 aHicks, Andrew, A1 aHengstenberg, Christian1 aHeid, Iris, M1 aHayward, Caroline1 aHavulinna, Aki, S1 aHastie, Nicholas, D1 aHarris, Tamara, B1 aHaritunians, Talin1 aHall, Alistair, S1 aGyllensten, Ulf1 aGuiducci, Candace1 aGroop, Leif, C1 aGonzalez, Elena1 aGieger, Christian1 aFreimer, Nelson, B1 aFerrucci, Luigi1 aErdmann, Jeanette1 aElliott, Paul1 aEjebe, Kenechi, G1 aDöring, Angela1 aDominiczak, Anna, F1 aDemissie, Serkalem1 aDeloukas, Panagiotis1 aGeus, Eco, J C1 ade Faire, Ulf1 aCrawford, Gabriel1 aCollins, Francis, S1 aChen, Yii-der, I1 aCaulfield, Mark, J1 aCampbell, Harry1 aBurtt, Noel, P1 aBonnycastle, Lori, L1 aBoomsma, Dorret, I1 aBoekholdt, Matthijs1 aBergman, Richard, N1 aBarroso, Inês1 aBandinelli, Stefania1 aBallantyne, Christie, M1 aAssimes, Themistocles, L1 aQuertermous, Thomas1 aAltshuler, David1 aSeielstad, Mark1 aWong, Tien, Y1 aTai, E-Shyong1 aFeranil, Alan, B1 aKuzawa, Christopher, W1 aAdair, Linda, S1 aTaylor, Herman, A1 aBorecki, Ingrid, B1 aGabriel, Stacey, B1 aWilson, James, G1 aHolm, Hilma1 aThorsteinsdottir, Unnur1 aGudnason, Vilmundur1 aKrauss, Ronald, M1 aMohlke, Karen, L1 aOrdovas, Jose, M1 aMunroe, Patricia, B1 aKooner, Jaspal, S1 aTall, Alan, R1 aHegele, Robert, A1 aKastelein, John, J P1 aSchadt, Eric, E1 aRotter, Jerome, I1 aBoerwinkle, Eric1 aStrachan, David, P1 aMooser, Vincent1 aStefansson, Kari1 aReilly, Muredach, P1 aSamani, Nilesh, J1 aSchunkert, Heribert1 aCupples, Adrienne, L1 aSandhu, Manjinder, S1 aRidker, Paul, M1 aRader, Daniel, J1 aDuijn, Cornelia, M1 aPeltonen, Leena1 aAbecasis, Goncalo, R1 aBoehnke, Michael1 aKathiresan, Sekar uhttps://chs-nhlbi.org/node/122104142nas a2200757 4500008004100000022001400041245008700055210006900142260001300211300001100224490000600235520194100241653002202182653002102204653002102225653001902246653002302265653004002288653003202328653001302360653001102373653001402384653001902398653003602417653002002453653001802473100002002491700002202511700001802533700002302551700002602574700002202600700002402622700001602646700002002662700001802682700002102700700001902721700002202740700002402762700002502786700002002811700001802831700002302849700002402872700002902896700002302925700002002948700002802968700002102996700002003017700002103037700001903058700002103077700002203098700002203120700002203142700002703164700002103191700002203212700002403234700002103258700002303279710004603302856003603348 2010 eng d a1942-326800aCandidate gene association resource (CARe): design, methods, and proof of concept.0 aCandidate gene association resource CARe design methods and proo c2010 Jun a267-750 v33 aBACKGROUND: The National Heart, Lung, and Blood Institute's Candidate Gene Association Resource (CARe), a planned cross-cohort analysis of genetic variation in cardiovascular, pulmonary, hematologic, and sleep-related traits, comprises >40,000 participants representing 4 ethnic groups in 9 community-based cohorts. The goals of CARe include the discovery of new variants associated with traits using a candidate gene approach and the discovery of new variants using the genome-wide association mapping approach specifically in African Americans.
METHODS AND RESULTS: CARe has assembled DNA samples for >40,000 individuals self-identified as European American, African American, Hispanic, or Chinese American, with accompanying data on hundreds of phenotypes that have been standardized and deposited in the CARe Phenotype Database. All participants were genotyped for 7 single-nucleotide polymorphisms (SNPs) selected based on prior association evidence. We performed association analyses relating each of these SNPs to lipid traits, stratified by sex and ethnicity, and adjusted for age and age squared. In at least 2 of the ethnic groups, SNPs near CETP, LIPC, and LPL strongly replicated for association with high-density lipoprotein cholesterol concentrations, PCSK9 with low-density lipoprotein cholesterol levels, and LPL and APOA5 with serum triglycerides. Notably, some SNPs showed varying effect sizes and significance of association in different ethnic groups.
CONCLUSIONS: The CARe Pilot Study validates the operational framework for phenotype collection, SNP genotyping, and analytic pipeline of the CARe project and validates the planned candidate gene study of approximately 2000 biological candidate loci in all participants and genome-wide association study in approximately 8000 African American participants. CARe will serve as a valuable resource for the scientific community.
10aAfrican Americans10aCholesterol, HDL10aCholesterol, LDL10aCohort Studies10aDatabases, Genetic10aEuropean Continental Ancestry Group10aGenetic Association Studies10aGenotype10aHumans10aPhenotype10aPilot Projects10aPolymorphism, Single Nucleotide10aResearch Design10aTriglycerides1 aMusunuru, Kiran1 aLettre, Guillaume1 aYoung, Taylor1 aFarlow, Deborah, N1 aPirruccello, James, P1 aEjebe, Kenechi, G1 aKeating, Brendan, J1 aYang, Qiong1 aChen, Ming-Huei1 aLapchyk, Nina1 aCrenshaw, Andrew1 aZiaugra, Liuda1 aRachupka, Anthony1 aBenjamin, Emelia, J1 aCupples, Adrienne, L1 aFornage, Myriam1 aFox, Ervin, R1 aHeckbert, Susan, R1 aHirschhorn, Joel, N1 aNewton-Cheh, Christopher1 aNizzari, Marcia, M1 aPaltoo, Dina, N1 aPapanicolaou, George, J1 aPatel, Sanjay, R1 aPsaty, Bruce, M1 aRader, Daniel, J1 aRedline, Susan1 aRich, Stephen, S1 aRotter, Jerome, I1 aTaylor, Herman, A1 aTracy, Russell, P1 aVasan, Ramachandran, S1 aWilson, James, G1 aKathiresan, Sekar1 aFabsitz, Richard, R1 aBoerwinkle, Eric1 aGabriel, Stacey, B1 aNHLBI Candidate Gene Association Resource uhttps://chs-nhlbi.org/node/118805521nas a2201561 4500008004100000022001400041245010000055210006900155260001300224300001200237490000700249520109100256653001201347653002101359653002301380653002601403653002401429653001701453653003401470653002801504653001101532653000901543653002101552653001901573653002201592653004001614653003601654653002001690100002201710700001801732700002501750700001801775700002901793700001901822700001501841700002101856700002201877700001901899700002101918700002501939700002201964700002601986700001902012700002302031700001702054700002202071700002602093700001802119700002002137700002202157700001202179700001902191700002602210700001902236700001902255700001802274700001802292700001902310700001802329700001802347700002702365700001902392700002402411700001902435700001702454700002002471700002702491700001702518700002602535700002202561700001702583700002302600700002202623700002402645700002402669700002002693700001902713700002502732700002002757700002302777700002802800700001902828700002402847700001702871700002102888700002402909700002202933700002002955700001702975700002202992700001903014700003003033700002103063700002003084700002303104700002203127700001903149700002003168700002103188700002803209700002903237700003003266700002603296700002303322700002103345700001903366700001603385700001703401700002603418700002403444700002203468700002203490700002903512700002003541700002003561700001803581700001603599700002003615700002103635700002603656700002403682700002003706700002403726700002303750700002203773700002203795700002003817700002603837700002203863700001903885700001903904856003603923 2010 eng d a1546-171800aCommon variants in 22 loci are associated with QRS duration and cardiac ventricular conduction.0 aCommon variants in 22 loci are associated with QRS duration and c2010 Dec a1068-760 v423 aThe QRS interval, from the beginning of the Q wave to the end of the S wave on an electrocardiogram, reflects ventricular depolarization and conduction time and is a risk factor for mortality, sudden death and heart failure. We performed a genome-wide association meta-analysis in 40,407 individuals of European descent from 14 studies, with further genotyping in 7,170 additional Europeans, and we identified 22 loci associated with QRS duration (P < 5 × 10(-8)). These loci map in or near genes in pathways with established roles in ventricular conduction such as sodium channels, transcription factors and calcium-handling proteins, but also point to previously unidentified biologic processes, such as kinase inhibitors and genes related to tumorigenesis. We demonstrate that SCN10A, a candidate gene at the most significantly associated locus in this study, is expressed in the mouse ventricular conduction system, and treatment with a selective SCN10A blocker prolongs QRS duration. These findings extend our current knowledge of ventricular depolarization and conduction.
10aAnimals10aAnimals, Newborn10aChromosomes, Human10aComputational Biology10aElectrocardiography10aGenetic Loci10aGenome-Wide Association Study10aHeart Conduction System10aHumans10aMice10aMice, Transgenic10aModels, Animal10aMyocytes, Cardiac10aNAV1.8 Voltage-Gated Sodium Channel10aPolymorphism, Single Nucleotide10aSodium Channels1 aSotoodehnia, Nona1 aIsaacs, Aaron1 ade Bakker, Paul, I W1 aDörr, Marcus1 aNewton-Cheh, Christopher1 aNolte, Ilja, M1 aHarst, Pim1 aMüller, Martina1 aEijgelsheim, Mark1 aAlonso, Alvaro1 aHicks, Andrew, A1 aPadmanabhan, Sandosh1 aHayward, Caroline1 aSmith, Albert, Vernon1 aPolasek, Ozren1 aGiovannone, Steven1 aFu, Jingyuan1 aMagnani, Jared, W1 aMarciante, Kristin, D1 aPfeufer, Arne1 aGharib, Sina, A1 aTeumer, Alexander1 aLi, Man1 aBis, Joshua, C1 aRivadeneira, Fernando1 aAspelund, Thor1 aKöttgen, Anna1 aJohnson, Toby1 aRice, Kenneth1 aSie, Mark, P S1 aWang, Ying, A1 aKlopp, Norman1 aFuchsberger, Christian1 aWild, Sarah, H1 aLeach, Irene, Mateo1 aEstrada, Karol1 aVölker, Uwe1 aWright, Alan, F1 aAsselbergs, Folkert, W1 aQu, Jiaxiang1 aChakravarti, Aravinda1 aSinner, Moritz, F1 aKors, Jan, A1 aPetersmann, Astrid1 aHarris, Tamara, B1 aSoliman, Elsayed, Z1 aMunroe, Patricia, B1 aPsaty, Bruce, M1 aOostra, Ben, A1 aCupples, Adrienne, L1 aPerz, Siegfried1 ade Boer, Rudolf, A1 aUitterlinden, André, G1 aVölzke, Henry1 aSpector, Timothy, D1 aLiu, Fang-Yu1 aBoerwinkle, Eric1 aDominiczak, Anna, F1 aRotter, Jerome, I1 avan Herpen, Gé1 aLevy, Daniel1 aWichmann, H-Erich1 aGilst, Wiek, H1 aWitteman, Jacqueline, C M1 aKroemer, Heyo, K1 aKao, Linda, W H1 aHeckbert, Susan, R1 aMeitinger, Thomas1 aHofman, Albert1 aCampbell, Harry1 aFolsom, Aaron, R1 avan Veldhuisen, Dirk, J1 aSchwienbacher, Christine1 aO'Donnell, Christopher, J1 aVolpato, Claudia, Beu1 aCaulfield, Mark, J1 aConnell, John, M1 aLauner, Lenore1 aLu, Xiaowen1 aFranke, Lude1 aFehrmann, Rudolf, S N1 aMeerman, Gerard, te1 aGroen, Harry, J M1 aWeersma, Rinse, K1 avan den Berg, Leonard, H1 aWijmenga, Cisca1 aOphoff, Roel, A1 aNavis, Gerjan1 aRudan, Igor1 aSnieder, Harold1 aWilson, James, F1 aPramstaller, Peter, P1 aSiscovick, David, S1 aWang, Thomas, J1 aGudnason, Vilmundur1 aDuijn, Cornelia, M1 aFelix, Stephan, B1 aFishman, Glenn, I1 aJamshidi, Yalda1 aStricker, Bruno, H Ch1 aSamani, Nilesh, J1 aKääb, Stefan1 aArking, Dan, E uhttps://chs-nhlbi.org/node/124404080nas a2200757 4500008004100000022001400041245019100055210006900246260001300315300001100328490000600339520181900345653002202164653000902186653002202195653001502217653001902232653004002251653001102291653003402302653001302336653001802349653001102367653001202378653000902390653003802399653002202437653001602459653003602475653001702511100002402528700002102552700002502573700002202598700002002620700001902640700002302659700001902682700002302701700002402724700001802748700002302766700002102789700002602810700002402836700001902860700001802879700002302897700003002920700002102950700002302971700001902994700001703013700002203030700001803052700002803070700002003098700002003118700002403138700002303162700002103185700003003206700002703236700002303263856003603286 2010 eng d a1942-326800aGenomic variation associated with mortality among adults of European and African ancestry with heart failure: the cohorts for heart and aging research in genomic epidemiology consortium.0 aGenomic variation associated with mortality among adults of Euro c2010 Jun a248-550 v33 aBACKGROUND: Prognosis and survival are significant concerns for individuals with heart failure (HF). To better understand the pathophysiology of HF prognosis, the association between 2,366,858 single-nucleotide polymorphisms (SNPs) and all-cause mortality was evaluated among individuals with incident HF from 4 community-based prospective cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study.
METHODS AND RESULTS: Participants were 2526 individuals of European ancestry and 466 individuals of African ancestry who experienced an incident HF event during follow-up in the respective cohorts. Within each study, the association between genetic variants and time to mortality among individuals with HF was assessed by Cox proportional hazards models that included adjustment for sex and age at the time of the HF event. Prospective fixed-effect meta-analyses were conducted for the 4 study populations of European ancestry (N=1645 deaths) and for the 2 populations of African ancestry (N=281 deaths). Genome-wide significance was set at P=5.0x10(-7). Meta-analytic findings among individuals of European ancestry revealed 1 genome-wide significant locus on chromosome 3p22 in an intron of CKLF-like MARVEL transmembrane domain containing 7 (CMTM7, P=3.2x10(-7)). Eight additional loci in individuals of European ancestry and 4 loci in individuals of African ancestry were identified by high-signal SNPs (P<1.0x10(-5)) but did not meet genome-wide significance.
CONCLUSIONS: This study identified a novel locus associated with all-cause mortality among individuals of European ancestry with HF. This finding warrants additional investigation, including replication, in other studies of HF.
10aAfrican Americans10aAged10aAged, 80 and over10aChemokines10aCohort Studies10aEuropean Continental Ancestry Group10aFemale10aGenome-Wide Association Study10aGenotype10aHeart Failure10aHumans10aIntrons10aMale10aMARVEL Domain-Containing Proteins10aMembrane Proteins10aMiddle Aged10aPolymorphism, Single Nucleotide10aRisk Factors1 aMorrison, Alanna, C1 aFelix, Janine, F1 aCupples, Adrienne, L1 aGlazer, Nicole, L1 aLoehr, Laura, R1 aDehghan, Abbas1 aDemissie, Serkalem1 aBis, Joshua, C1 aRosamond, Wayne, D1 aAulchenko, Yurii, S1 aWang, Ying, A1 aHaritunians, Talin1 aFolsom, Aaron, R1 aRivadeneira, Fernando1 aBenjamin, Emelia, J1 aLumley, Thomas1 aCouper, David1 aStricker, Bruno, H1 aO'Donnell, Christopher, J1 aRice, Kenneth, M1 aChang, Patricia, P1 aHofman, Albert1 aLevy, Daniel1 aRotter, Jerome, I1 aFox, Ervin, R1 aUitterlinden, André, G1 aWang, Thomas, J1 aPsaty, Bruce, M1 aWillerson, James, T1 aDuijn, Cornelia, M1 aBoerwinkle, Eric1 aWitteman, Jacqueline, C M1 aVasan, Ramachandran, S1 aSmith, Nicholas, L uhttps://chs-nhlbi.org/node/118712698nas a2203781 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2010 eng d a1476-468700aHundreds of variants clustered in genomic loci and biological pathways affect human height.0 aHundreds of variants clustered in genomic loci and biological pa c2010 Oct 14 a832-80 v4673 aMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
10aBody Height10aChromosomes, Human, Pair 310aGenetic Loci10aGenetic Predisposition to Disease10aGenome, Human10aGenome-Wide Association Study10aHumans10aMetabolic Networks and Pathways10aMultifactorial Inheritance10aPhenotype10aPolymorphism, Single Nucleotide1 aAllen, Hana, Lango1 aEstrada, Karol1 aLettre, Guillaume1 aBerndt, Sonja, I1 aWeedon, Michael, N1 aRivadeneira, Fernando1 aWiller, Cristen, J1 aJackson, Anne, U1 aVedantam, Sailaja1 aRaychaudhuri, Soumya1 aFerreira, Teresa1 aWood, Andrew, R1 aWeyant, Robert, J1 aSegrè, Ayellet, V1 aSpeliotes, Elizabeth, K1 aWheeler, Eleanor1 aSoranzo, Nicole1 aPark, Ju-Hyun1 aYang, Jian1 aGudbjartsson, Daniel1 aHeard-Costa, Nancy, L1 aRandall, Joshua, C1 aQi, Lu1 aSmith, Albert, Vernon1 aMägi, Reedik1 aPastinen, Tomi1 aLiang, Liming1 aHeid, Iris, M1 aLuan, Jian'an1 aThorleifsson, Gudmar1 aWinkler, Thomas, W1 aGoddard, Michael, E1 aLo, Ken, Sin1 aPalmer, Cameron1 aWorkalemahu, Tsegaselassie1 aAulchenko, Yurii, S1 aJohansson, Asa1 aZillikens, Carola, M1 aFeitosa, Mary, F1 aEsko, Tõnu1 aJohnson, Toby1 aKetkar, Shamika1 aKraft, Peter1 aMangino, Massimo1 aProkopenko, Inga1 aAbsher, Devin1 aAlbrecht, Eva1 aErnst, Florian1 aGlazer, Nicole, L1 aHayward, Caroline1 aHottenga, Jouke-Jan1 aJacobs, Kevin, B1 aKnowles, Joshua, W1 aKutalik, Zoltán1 aMonda, Keri, L1 aPolasek, Ozren1 aPreuss, Michael1 aRayner, Nigel, W1 aRobertson, Neil, R1 aSteinthorsdottir, Valgerdur1 aTyrer, Jonathan, P1 aVoight, Benjamin, F1 aWiklund, Fredrik1 aXu, Jianfeng1 aZhao, Jing Hua1 aNyholt, Dale, R1 aPellikka, Niina1 aPerola, Markus1 aPerry, John, R B1 aSurakka, Ida1 aTammesoo, Mari-Liis1 aAltmaier, Elizabeth, L1 aAmin, Najaf1 aAspelund, Thor1 aBhangale, Tushar1 aBoucher, Gabrielle1 aChasman, Daniel, I1 aChen, Constance1 aCoin, Lachlan1 aCooper, Matthew, N1 aDixon, Anna, L1 aGibson, Quince1 aGrundberg, Elin1 aHao, Ke1 aJunttila, Juhani1 aKaplan, Lee, M1 aKettunen, Johannes1 aKönig, Inke, R1 aKwan, Tony1 aLawrence, Robert, W1 aLevinson, Douglas, F1 aLorentzon, Mattias1 aMcKnight, Barbara1 aMorris, Andrew, P1 aMüller, Martina1 aNgwa, Julius, Suh1 aPurcell, Shaun1 aRafelt, Suzanne1 aSalem, Rany, M1 aSalvi, Erika1 aSanna, Serena1 aShi, Jianxin1 aSovio, Ulla1 aThompson, John, R1 aTurchin, Michael, C1 aVandenput, Liesbeth1 aVerlaan, Dominique, J1 aVitart, Veronique1 aWhite, Charles, C1 aZiegler, Andreas1 aAlmgren, Peter1 aBalmforth, Anthony, J1 aCampbell, Harry1 aCitterio, Lorena1 aDe Grandi, Alessandro1 aDominiczak, Anna1 aDuan, Jubao1 aElliott, Paul1 aElosua, Roberto1 aEriksson, Johan, G1 aFreimer, Nelson, B1 aGeus, Eco, J C1 aGlorioso, Nicola1 aHaiqing, Shen1 aHartikainen, Anna-Liisa1 aHavulinna, Aki, S1 aHicks, Andrew, A1 aHui, Jennie1 aIgl, Wilmar1 aIllig, Thomas1 aJula, Antti1 aKajantie, Eero1 aKilpeläinen, Tuomas, O1 aKoiranen, Markku1 aKolcic, Ivana1 aKoskinen, Seppo1 aKovacs, Peter1 aLaitinen, Jaana1 aLiu, Jianjun1 aLokki, Marja-Liisa1 aMarusic, Ana1 aMaschio, Andrea1 aMeitinger, Thomas1 aMulas, Antonella1 aParé, Guillaume1 aParker, Alex, N1 aPeden, John, F1 aPetersmann, Astrid1 aPichler, Irene1 aPietiläinen, Kirsi, H1 aPouta, Anneli1 aRidderstråle, Martin1 aRotter, Jerome, I1 aSambrook, Jennifer, G1 aSanders, Alan, R1 aSchmidt, Carsten, Oliver1 aSinisalo, Juha1 aSmit, Jan, H1 aStringham, Heather, M1 aWalters, Bragi1 aWiden, Elisabeth1 aWild, Sarah, H1 aWillemsen, Gonneke1 aZagato, Laura1 aZgaga, Lina1 aZitting, Paavo1 aAlavere, Helene1 aFarrall, Martin1 aMcArdle, Wendy, L1 aNelis, Mari1 aPeters, Marjolein, J1 aRipatti, Samuli1 avan Meurs, Joyce, B J1 aAben, Katja, K1 aArdlie, Kristin, G1 aBeckmann, Jacques, S1 aBeilby, John, P1 aBergman, Richard, N1 aBergmann, Sven1 aCollins, Francis, S1 aCusi, Daniele1 aHeijer, Martin, den1 aEiriksdottir, Gudny1 aGejman, Pablo, V1 aHall, Alistair, S1 aHamsten, Anders1 aHuikuri, Heikki, V1 aIribarren, Carlos1 aKähönen, Mika1 aKaprio, Jaakko1 aKathiresan, Sekar1 aKiemeney, Lambertus1 aKocher, Thomas1 aLauner, Lenore, J1 aLehtimäki, Terho1 aMelander, Olle1 aMosley, Tom, H1 aMusk, Arthur, W1 aNieminen, Markku, S1 aO'Donnell, Christopher, J1 aOhlsson, Claes1 aOostra, Ben1 aPalmer, Lyle, J1 aRaitakari, Olli1 aRidker, Paul, M1 aRioux, John, D1 aRissanen, Aila1 aRivolta, Carlo1 aSchunkert, Heribert1 aShuldiner, Alan, R1 aSiscovick, David, S1 aStumvoll, Michael1 aTönjes, Anke1 aTuomilehto, Jaakko1 avan Ommen, Gert-Jan1 aViikari, Jorma1 aHeath, Andrew, C1 aMartin, Nicholas, G1 aMontgomery, Grant, W1 aProvince, Michael, A1 aKayser, Manfred1 aArnold, Alice, M1 aAtwood, Larry, D1 aBoerwinkle, Eric1 aChanock, Stephen, J1 aDeloukas, Panos1 aGieger, Christian1 aGrönberg, Henrik1 aHall, Per1 aHattersley, Andrew, T1 aHengstenberg, Christian1 aHoffman, Wolfgang1 aLathrop, Mark, G1 aSalomaa, Veikko1 aSchreiber, Stefan1 aUda, Manuela1 aWaterworth, Dawn1 aWright, Alan, F1 aAssimes, Themistocles, L1 aBarroso, Inês1 aHofman, Albert1 aMohlke, Karen, L1 aBoomsma, Dorret, I1 aCaulfield, Mark, J1 aCupples, Adrienne, L1 aErdmann, Jeanette1 aFox, Caroline, S1 aGudnason, Vilmundur1 aGyllensten, Ulf1 aHarris, Tamara, B1 aHayes, Richard, B1 aJarvelin, Marjo-Riitta1 aMooser, Vincent1 aMunroe, Patricia, B1 aOuwehand, Willem, H1 aPenninx, Brenda, W1 aPramstaller, Peter, P1 aQuertermous, Thomas1 aRudan, Igor1 aSamani, Nilesh, J1 aSpector, Timothy, D1 aVölzke, Henry1 aWatkins, Hugh1 aWilson, James, F1 aGroop, Leif, C1 aHaritunians, Talin1 aHu, Frank, B1 aKaplan, Robert, C1 aMetspalu, Andres1 aNorth, Kari, E1 aSchlessinger, David1 aWareham, Nicholas, J1 aHunter, David, J1 aO'Connell, Jeffrey, R1 aStrachan, David, P1 aWichmann, H-Erich1 aBorecki, Ingrid, B1 aDuijn, Cornelia, M1 aSchadt, Eric, E1 aThorsteinsdottir, Unnur1 aPeltonen, Leena1 aUitterlinden, André, G1 aVisscher, Peter, M1 aChatterjee, Nilanjan1 aLoos, Ruth, J F1 aBoehnke, Michael1 aMcCarthy, Mark, I1 aIngelsson, Erik1 aLindgren, Cecilia, M1 aAbecasis, Goncalo, R1 aStefansson, Kari1 aFrayling, Timothy, M1 aHirschhorn, Joel, N uhttps://chs-nhlbi.org/node/123405042nas a2201093 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2010 eng d a1935-554800aInteractions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies.0 aInteractions of dietary wholegrain intake with fasting glucose a c2010 Dec a2684-910 v333 aOBJECTIVE: Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin.
RESEARCH DESIGN AND METHODS: Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant.
RESULTS: Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele.
CONCLUSIONS: Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.
10aAdult10aAged10aBlood Glucose10aEdible Grain10aEuropean Continental Ancestry Group10aFasting10aFemale10aGenetic Loci10aGenome-Wide Association Study10aGenotype10aHumans10aInsulin10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide1 aNettleton, Jennifer, A1 aMcKeown, Nicola, M1 aKanoni, Stavroula1 aLemaitre, Rozenn, N1 aHivert, Marie-France1 aNgwa, Julius1 avan Rooij, Frank, J A1 aSonestedt, Emily1 aWojczynski, Mary, K1 aYe, Zheng1 aTanaka, Tosh1 aGarcia, Melissa1 aAnderson, Jennifer, S1 aFollis, Jack, L1 aDjoussé, Luc1 aMukamal, Kenneth1 aPapoutsakis, Constantina1 aMozaffarian, Dariush1 aZillikens, Carola, M1 aBandinelli, Stefania1 aBennett, Amanda, J1 aBorecki, Ingrid, B1 aFeitosa, Mary, F1 aFerrucci, Luigi1 aForouhi, Nita, G1 aGroves, Christopher, J1 aHallmans, Göran1 aHarris, Tamara1 aHofman, Albert1 aHouston, Denise, K1 aHu, Frank, B1 aJohansson, Ingegerd1 aKritchevsky, Stephen, B1 aLangenberg, Claudia1 aLauner, Lenore1 aLiu, Yongmei1 aLoos, Ruth, J1 aNalls, Michael1 aOrho-Melander, Marju1 aRenstrom, Frida1 aRice, Kenneth1 aRiserus, Ulf1 aRolandsson, Olov1 aRotter, Jerome, I1 aSaylor, Georgia1 aSijbrands, Eric, J G1 aSjogren, Per1 aSmith, Albert1 aSteingrímsdóttir, Laufey1 aUitterlinden, André, G1 aWareham, Nicholas, J1 aProkopenko, Inga1 aPankow, James, S1 aDuijn, Cornelia, M1 aFlorez, Jose, C1 aWitteman, Jacqueline, C M1 aDupuis, Josée1 aDedoussis, George, V1 aOrdovas, Jose, M1 aIngelsson, Erik1 aCupples, Adrienne, L1 aSiscovick, David, S1 aFranks, Paul, W1 aMeigs, James, B1 aMAGIC investigators uhttps://chs-nhlbi.org/node/122211930nas a2203889 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2010 eng d a1546-171800aMeta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution.0 aMetaanalysis identifies 13 new loci associated with waisthip rat c2010 Nov a949-600 v423 aWaist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
10aAdipose Tissue10aAge Factors10aChromosome Mapping10aFemale10aGenome, Human10aGenome-Wide Association Study10aHumans10aMale10aMeta-Analysis as Topic10aPolymorphism, Single Nucleotide10aSex Characteristics10aWaist-Hip Ratio1 aHeid, Iris, M1 aJackson, Anne, U1 aRandall, Joshua, C1 aWinkler, Thomas, W1 aQi, Lu1 aSteinthorsdottir, Valgerdur1 aThorleifsson, Gudmar1 aZillikens, Carola, M1 aSpeliotes, Elizabeth, K1 aMägi, Reedik1 aWorkalemahu, Tsegaselassie1 aWhite, Charles, C1 aBouatia-Naji, Nabila1 aHarris, Tamara, B1 aBerndt, Sonja, I1 aIngelsson, Erik1 aWiller, Cristen, J1 aWeedon, Michael, N1 aLuan, Jian'an1 aVedantam, Sailaja1 aEsko, Tõnu1 aKilpeläinen, Tuomas, O1 aKutalik, Zoltán1 aLi, Shengxu1 aMonda, Keri, L1 aDixon, Anna, L1 aHolmes, Christopher, C1 aKaplan, Lee, M1 aLiang, Liming1 aMin, Josine, L1 aMoffatt, Miriam, F1 aMolony, Cliona1 aNicholson, George1 aSchadt, Eric, E1 aZondervan, Krina, T1 aFeitosa, Mary, F1 aFerreira, Teresa1 aAllen, Hana, Lango1 aWeyant, Robert, J1 aWheeler, Eleanor1 aWood, Andrew, R1 aEstrada, Karol1 aGoddard, Michael, E1 aLettre, Guillaume1 aMangino, Massimo1 aNyholt, Dale, R1 aPurcell, Shaun1 aSmith, Albert, Vernon1 aVisscher, Peter, M1 aYang, Jian1 aMcCarroll, Steven, A1 aNemesh, James1 aVoight, Benjamin, F1 aAbsher, Devin1 aAmin, Najaf1 aAspelund, Thor1 aCoin, Lachlan1 aGlazer, Nicole, L1 aHayward, Caroline1 aHeard-Costa, Nancy, L1 aHottenga, Jouke-Jan1 aJohansson, Asa1 aJohnson, Toby1 aKaakinen, Marika1 aKapur, Karen1 aKetkar, Shamika1 aKnowles, Joshua, W1 aKraft, Peter1 aKraja, Aldi, T1 aLamina, Claudia1 aLeitzmann, Michael, F1 aMcKnight, Barbara1 aMorris, Andrew, P1 aOng, Ken, K1 aPerry, John, R B1 aPeters, Marjolein, J1 aPolasek, Ozren1 aProkopenko, Inga1 aRayner, Nigel, W1 aRipatti, Samuli1 aRivadeneira, Fernando1 aRobertson, Neil, R1 aSanna, Serena1 aSovio, Ulla1 aSurakka, Ida1 aTeumer, Alexander1 avan Wingerden, Sophie1 aVitart, Veronique1 aZhao, Jing Hua1 aCavalcanti-Proença, Christine1 aChines, Peter, S1 aFisher, Eva1 aKulzer, Jennifer, R1 aLecoeur, Cécile1 aNarisu, Narisu1 aSandholt, Camilla1 aScott, Laura, J1 aSilander, Kaisa1 aStark, Klaus1 aTammesoo, Mari-Liis1 aTeslovich, Tanya, M1 aTimpson, Nicholas, John1 aWatanabe, Richard, M1 aWelch, Ryan1 aChasman, Daniel, I1 aCooper, Matthew, N1 aJansson, John-Olov1 aKettunen, Johannes1 aLawrence, Robert, W1 aPellikka, Niina1 aPerola, Markus1 aVandenput, Liesbeth1 aAlavere, Helene1 aAlmgren, Peter1 aAtwood, Larry, D1 aBennett, Amanda, J1 aBiffar, Reiner1 aBonnycastle, Lori, L1 aBornstein, Stefan, R1 aBuchanan, Thomas, A1 aCampbell, Harry1 aDay, Ian, N M1 aDei, Mariano1 aDörr, Marcus1 aElliott, Paul1 aErdos, Michael, R1 aEriksson, Johan, G1 aFreimer, Nelson, B1 aFu, Mao1 aGaget, Stefan1 aGeus, Eco, J C1 aGjesing, Anette, P1 aGrallert, Harald1 aGrässler, Jürgen1 aGroves, Christopher, J1 aGuiducci, Candace1 aHartikainen, Anna-Liisa1 aHassanali, Neelam1 aHavulinna, Aki, S1 aHerzig, Karl-Heinz1 aHicks, Andrew, A1 aHui, Jennie1 aIgl, Wilmar1 aJousilahti, Pekka1 aJula, Antti1 aKajantie, Eero1 aKinnunen, Leena1 aKolcic, Ivana1 aKoskinen, Seppo1 aKovacs, Peter1 aKroemer, Heyo, K1 aKrzelj, Vjekoslav1 aKuusisto, Johanna1 aKvaloy, Kirsti1 aLaitinen, Jaana1 aLantieri, Olivier1 aLathrop, Mark, G1 aLokki, Marja-Liisa1 aLuben, Robert, N1 aLudwig, Barbara1 aMcArdle, Wendy, L1 aMcCarthy, Anne1 aMorken, Mario, A1 aNelis, Mari1 aNeville, Matt, J1 aParé, Guillaume1 aParker, Alex, N1 aPeden, John, F1 aPichler, Irene1 aPietiläinen, Kirsi, H1 aPlatou, Carl, G P1 aPouta, Anneli1 aRidderstråle, Martin1 aSamani, Nilesh, J1 aSaramies, Jouko1 aSinisalo, Juha1 aSmit, Jan, H1 aStrawbridge, Rona, J1 aStringham, Heather, M1 aSwift, Amy, J1 aTeder-Laving, Maris1 aThomson, Brian1 aUsala, Gianluca1 avan Meurs, Joyce, B J1 avan Ommen, Gert-Jan1 aVatin, Vincent1 aVolpato, Claudia, B1 aWallaschofski, Henri1 aWalters, Bragi, G1 aWiden, Elisabeth1 aWild, Sarah, H1 aWillemsen, Gonneke1 aWitte, Daniel, R1 aZgaga, Lina1 aZitting, Paavo1 aBeilby, John, P1 aJames, Alan, L1 aKähönen, Mika1 aLehtimäki, Terho1 aNieminen, Markku, S1 aOhlsson, Claes1 aPalmer, Lyle, J1 aRaitakari, Olli1 aRidker, Paul, M1 aStumvoll, Michael1 aTönjes, Anke1 aViikari, Jorma1 aBalkau, Beverley1 aBen-Shlomo, Yoav1 aBergman, Richard, N1 aBoeing, Heiner1 aSmith, George Davey1 aEbrahim, Shah1 aFroguel, Philippe1 aHansen, Torben1 aHengstenberg, Christian1 aHveem, Kristian1 aIsomaa, Bo1 aJørgensen, Torben1 aKarpe, Fredrik1 aKhaw, Kay-Tee1 aLaakso, Markku1 aLawlor, Debbie, A1 aMarre, Michel1 aMeitinger, Thomas1 aMetspalu, Andres1 aMidthjell, Kristian1 aPedersen, Oluf1 aSalomaa, Veikko1 aSchwarz, Peter, E H1 aTuomi, Tiinamaija1 aTuomilehto, Jaakko1 aValle, Timo, T1 aWareham, Nicholas, J1 aArnold, Alice, M1 aBeckmann, Jacques, S1 aBergmann, Sven1 aBoerwinkle, Eric1 aBoomsma, Dorret, I1 aCaulfield, Mark, J1 aCollins, Francis, S1 aEiriksdottir, Gudny1 aGudnason, Vilmundur1 aGyllensten, Ulf1 aHamsten, Anders1 aHattersley, Andrew, T1 aHofman, Albert1 aHu, Frank, B1 aIllig, Thomas1 aIribarren, Carlos1 aJarvelin, Marjo-Riitta1 aKao, Linda, W H1 aKaprio, Jaakko1 aLauner, Lenore, J1 aMunroe, Patricia, B1 aOostra, Ben1 aPenninx, Brenda, W1 aPramstaller, Peter, P1 aPsaty, Bruce, M1 aQuertermous, Thomas1 aRissanen, Aila1 aRudan, Igor1 aShuldiner, Alan, R1 aSoranzo, Nicole1 aSpector, Timothy, D1 aSyvänen, Ann-Christine1 aUda, Manuela1 aUitterlinden, Andre1 aVölzke, Henry1 aVollenweider, Peter1 aWilson, James, F1 aWitteman, Jacqueline, C1 aWright, Alan, F1 aAbecasis, Goncalo, R1 aBoehnke, Michael1 aBorecki, Ingrid, B1 aDeloukas, Panos1 aFrayling, Timothy, M1 aGroop, Leif, C1 aHaritunians, Talin1 aHunter, David, J1 aKaplan, Robert, C1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aPeltonen, Leena1 aSchlessinger, David1 aStrachan, David, P1 aHirschhorn, Joel, N1 aAssimes, Themistocles, L1 aWichmann, H-Erich1 aThorsteinsdottir, Unnur1 aDuijn, Cornelia, M1 aStefansson, Kari1 aCupples, Adrienne, L1 aLoos, Ruth, J F1 aBarroso, Inês1 aMcCarthy, Mark, I1 aFox, Caroline, S1 aMohlke, Karen, L1 aLindgren, Cecilia, M1 aMAGIC uhttps://chs-nhlbi.org/node/123605938nas a2201621 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2011 eng d a1533-345000aCUBN is a gene locus for albuminuria.0 aCUBN is a gene locus for albuminuria c2011 Mar a555-700 v223 aIdentification of genetic risk factors for albuminuria may alter strategies for early prevention of CKD progression, particularly among patients with diabetes. Little is known about the influence of common genetic variants on albuminuria in both general and diabetic populations. We performed a meta-analysis of data from 63,153 individuals of European ancestry with genotype information from genome-wide association studies (CKDGen Consortium) and from a large candidate gene study (CARe Consortium) to identify susceptibility loci for the quantitative trait urinary albumin-to-creatinine ratio (UACR) and the clinical diagnosis microalbuminuria. We identified an association between a missense variant (I2984V) in the CUBN gene, which encodes cubilin, and both UACR (P = 1.1 × 10(-11)) and microalbuminuria (P = 0.001). We observed similar associations among 6981 African Americans in the CARe Consortium. The associations between this variant and both UACR and microalbuminuria were significant in individuals of European ancestry regardless of diabetes status. Finally, this variant associated with a 41% increased risk for the development of persistent microalbuminuria during 20 years of follow-up among 1304 participants with type 1 diabetes in the prospective DCCT/EDIC Study. In summary, we identified a missense CUBN variant that associates with levels of albuminuria in both the general population and in individuals with diabetes.
10aAfrican Continental Ancestry Group10aAlbuminuria10aEuropean Continental Ancestry Group10aGenetic Loci10aGenetic Predisposition to Disease10aHumans10aMutation, Missense10aReceptors, Cell Surface1 aBöger, Carsten, A1 aChen, Ming-Huei1 aTin, Adrienne1 aOlden, Matthias1 aKöttgen, Anna1 ade Boer, Ian, H1 aFuchsberger, Christian1 aO'Seaghdha, Conall, M1 aPattaro, Cristian1 aTeumer, Alexander1 aLiu, Ching-Ti1 aGlazer, Nicole, L1 aLi, Man1 aO'Connell, Jeffrey, R1 aTanaka, Toshiko1 aPeralta, Carmen, A1 aKutalik, Zoltán1 aLuan, Jian'an1 aZhao, Jing Hua1 aHwang, Shih-Jen1 aAkylbekova, Ermeg1 aKramer, Holly1 aHarst, Pim1 aSmith, Albert, V1 aLohman, Kurt1 ade Andrade, Mariza1 aHayward, Caroline1 aKollerits, Barbara1 aTönjes, Anke1 aAspelund, Thor1 aIngelsson, Erik1 aEiriksdottir, Gudny1 aLauner, Lenore, J1 aHarris, Tamara, B1 aShuldiner, Alan, R1 aMitchell, Braxton, D1 aArking, Dan, E1 aFranceschini, Nora1 aBoerwinkle, Eric1 aEgan, Josephine1 aHernandez, Dena1 aReilly, Muredach1 aTownsend, Raymond, R1 aLumley, Thomas1 aSiscovick, David, S1 aPsaty, Bruce, M1 aKestenbaum, Bryan1 aHaritunians, Talin1 aBergmann, Sven1 aVollenweider, Peter1 aWaeber, Gérard1 aMooser, Vincent1 aWaterworth, Dawn1 aJohnson, Andrew, D1 aFlorez, Jose, C1 aMeigs, James, B1 aLu, Xiaoning1 aTurner, Stephen, T1 aAtkinson, Elizabeth, J1 aLeak, Tennille, S1 aAasarød, Knut1 aSkorpen, Frank1 aSyvänen, Ann-Christine1 aIllig, Thomas1 aBaumert, Jens1 aKoenig, Wolfgang1 aKrämer, Bernhard, K1 aDevuyst, Olivier1 aMychaleckyj, Josyf, C1 aMinelli, Cosetta1 aBakker, Stephan, J L1 aKedenko, Lyudmyla1 aPaulweber, Bernhard1 aCoassin, Stefan1 aEndlich, Karlhans1 aKroemer, Heyo, K1 aBiffar, Reiner1 aStracke, Sylvia1 aVölzke, Henry1 aStumvoll, Michael1 aMägi, Reedik1 aCampbell, Harry1 aVitart, Veronique1 aHastie, Nicholas, D1 aGudnason, Vilmundur1 aKardia, Sharon, L R1 aLiu, Yongmei1 aPolasek, Ozren1 aCurhan, Gary1 aKronenberg, Florian1 aProkopenko, Inga1 aRudan, Igor1 aArnlöv, Johan1 aHallan, Stein1 aNavis, Gerjan1 aParsa, Afshin1 aFerrucci, Luigi1 aCoresh, Josef1 aShlipak, Michael, G1 aBull, Shelley, B1 aPaterson, Nicholas, J1 aWichmann, H-Erich1 aWareham, Nicholas, J1 aLoos, Ruth, J F1 aRotter, Jerome, I1 aPramstaller, Peter, P1 aCupples, Adrienne, L1 aBeckmann, Jacques, S1 aYang, Qiong1 aHeid, Iris, M1 aRettig, Rainer1 aDreisbach, Albert, W1 aBochud, Murielle1 aFox, Caroline, S1 aKao, W, H L1 aCKDGen Consortium uhttps://chs-nhlbi.org/node/127104476nas a2200937 4500008004100000022001400041245014100055210006900196260001300265300001300278490000600291520177500297653002202072653001502094653002102109653002302130653002102153653003002174653001102204653001902215653002202234653002502256653001802281653003402299653001302333653001102346653002702357653000902384653001502393653001402408653003602422653003302458653004702491653001302538100002102551700001802572700002202590700001802612700001702630700002002647700002002667700002002687700002402707700001802731700001702749700002102766700002502787700001602812700002502828700002302853700001902876700002102895700001602916700002802932700002402960700002802984700002003012700002203032700001503054700002003069700002303089700002103112700002203133700001903155700002203174700002403196700002203220700002803242700002303270700001903293700002003312700002403332700002403356700001703380700002703397700001703424700002003441700002103461700002003482856003603502 2011 eng d a1553-740400aEnhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.0 aEnhanced statistical tests for GWAS in admixed populations asses c2011 Apr ae10013710 v73 aWhile genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.
10aAfrican Americans10aAlgorithms10aBreast Neoplasms10aChromosome Mapping10aCoronary Disease10aDiabetes Mellitus, Type 210aFemale10aGene Frequency10aGenetic Variation10aGenetics, Population10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHumans10aLinkage Disequilibrium10aMale10aOdds Ratio10aPhenotype10aPolymorphism, Single Nucleotide10aPrincipal Component Analysis10aReceptor, Fibroblast Growth Factor, Type 210aSoftware1 aPasaniuc, Bogdan1 aZaitlen, Noah1 aLettre, Guillaume1 aChen, Gary, K1 aTandon, Arti1 aKao, Linda, W H1 aRuczinski, Ingo1 aFornage, Myriam1 aSiscovick, David, S1 aZhu, Xiaofeng1 aLarkin, Emma1 aLange, Leslie, A1 aCupples, Adrienne, L1 aYang, Qiong1 aAkylbekova, Ermeg, L1 aMusani, Solomon, K1 aDivers, Jasmin1 aMychaleckyj, Joe1 aLi, Mingyao1 aPapanicolaou, George, J1 aMillikan, Robert, C1 aAmbrosone, Christine, B1 aJohn, Esther, M1 aBernstein, Leslie1 aZheng, Wei1 aHu, Jennifer, J1 aZiegler, Regina, G1 aNyante, Sarah, J1 aBandera, Elisa, V1 aIngles, Sue, A1 aPress, Michael, F1 aChanock, Stephen, J1 aDeming, Sandra, L1 aRodriguez-Gil, Jorge, L1 aPalmer, Cameron, D1 aBuxbaum, Sarah1 aEkunwe, Lynette1 aHirschhorn, Joel, N1 aHenderson, Brian, E1 aMyers, Simon1 aHaiman, Christopher, A1 aReich, David1 aPatterson, Nick1 aWilson, James, G1 aPrice, Alkes, L uhttps://chs-nhlbi.org/node/128804453nas a2200889 4500008004100000022001400041245011700055210006900172260001300241300001300254490000600267520190600273653004202179653001002221653003902231653000902270653001202279653001102291653003002302653003202332653001702364653003402381653003102415653001102446653002802457653001102485653002802496653000902524653001602533653002202549653001402571653003602585653001402621100001802635700002202653700001802675700001902693700002302712700002302735700002002758700001702778700002402795700002002819700001902839700002002858700001802878700002102896700002902917700002102946700002202967700001802989700001603007700002303023700001203046700002403058700002503082700002303107700002303130700002303153700002303176700002203199700002203221700002303243700001703266700002403283700002203307700002403329700001803353700002503371700002503396700002303421700002503444700001503469700002103484710002203505856003603527 2011 eng d a1553-740400aGenetic association for renal traits among participants of African ancestry reveals new loci for renal function.0 aGenetic association for renal traits among participants of Afric c2011 Sep ae10022640 v73 aChronic kidney disease (CKD) is an increasing global public health concern, particularly among populations of African ancestry. We performed an interrogation of known renal loci, genome-wide association (GWA), and IBC candidate-gene SNP association analyses in African Americans from the CARe Renal Consortium. In up to 8,110 participants, we performed meta-analyses of GWA and IBC array data for estimated glomerular filtration rate (eGFR), CKD (eGFR <60 mL/min/1.73 m(2)), urinary albumin-to-creatinine ratio (UACR), and microalbuminuria (UACR >30 mg/g) and interrogated the 250 kb flanking region around 24 SNPs previously identified in European Ancestry renal GWAS analyses. Findings were replicated in up to 4,358 African Americans. To assess function, individually identified genes were knocked down in zebrafish embryos by morpholino antisense oligonucleotides. Expression of kidney-specific genes was assessed by in situ hybridization, and glomerular filtration was evaluated by dextran clearance. Overall, 23 of 24 previously identified SNPs had direction-consistent associations with eGFR in African Americans, 2 of which achieved nominal significance (UMOD, PIP5K1B). Interrogation of the flanking regions uncovered 24 new index SNPs in African Americans, 12 of which were replicated (UMOD, ANXA9, GCKR, TFDP2, DAB2, VEGFA, ATXN2, GATM, SLC22A2, TMEM60, SLC6A13, and BCAS3). In addition, we identified 3 suggestive loci at DOK6 (p-value = 5.3×10(-7)) and FNDC1 (p-value = 3.0×10(-7)) for UACR, and KCNQ1 with eGFR (p = 3.6×10(-6)). Morpholino knockdown of kcnq1 in the zebrafish resulted in abnormal kidney development and filtration capacity. We identified several SNPs in association with eGFR in African Ancestry individuals, as well as 3 suggestive loci for UACR and eGFR. Functional genetic studies support a role for kcnq1 in glomerular development in zebrafish.
10aAdaptor Proteins, Vesicular Transport10aAdult10aAfrican Continental Ancestry Group10aAged10aAnimals10aFemale10aGene Knockdown Techniques10aGenetic Association Studies10aGenetic Loci10aGenome-Wide Association Study10aGlomerular Filtration Rate10aHumans10aKCNQ1 Potassium Channel10aKidney10aKidney Failure, Chronic10aMale10aMiddle Aged10aNeoplasm Proteins10aPhenotype10aPolymorphism, Single Nucleotide10aZebrafish1 aLiu, Ching-Ti1 aGarnaas, Maija, K1 aTin, Adrienne1 aKöttgen, Anna1 aFranceschini, Nora1 aPeralta, Carmen, A1 ade Boer, Ian, H1 aLu, Xiaoning1 aAtkinson, Elizabeth1 aDing, Jingzhong1 aNalls, Michael1 aShriner, Daniel1 aCoresh, Josef1 aKutlar, Abdullah1 aBibbins-Domingo, Kirsten1 aSiscovick, David1 aAkylbekova, Ermeg1 aWyatt, Sharon1 aAstor, Brad1 aMychaleckjy, Josef1 aLi, Man1 aReilly, Muredach, P1 aTownsend, Raymond, R1 aAdeyemo, Adebowale1 aZonderman, Alan, B1 ade Andrade, Mariza1 aTurner, Stephen, T1 aMosley, Thomas, H1 aHarris, Tamara, B1 aRotimi, Charles, N1 aLiu, Yongmei1 aKardia, Sharon, L R1 aEvans, Michele, K1 aShlipak, Michael, G1 aKramer, Holly1 aFlessner, Michael, F1 aDreisbach, Albert, W1 aGoessling, Wolfram1 aCupples, Adrienne, L1 aKao, Linda1 aFox, Caroline, S1 aCKDGen Consortium uhttps://chs-nhlbi.org/node/132706039nas a2201765 4500008004100000022001400041245010100055210006900156260001600225300001100241490000700252520104700259653001601306653001401322653001201336653002601348653002001374653001601394653001101410653002201421653003401443653001101477653004001488653005001528653000901578653002201587653002701609653001501636653001201651653003601663653002101699100002801720700002501748700002501773700002501798700002001823700002401843700001801867700002501885700001801910700002401928700002601952700001701978700002601995700001902021700001602040700002202056700001802078700002302096700001202119700002102131700001802152700002702170700001902197700002102216700002202237700001302259700002102272700002402293700001902317700002002336700002502356700002202381700002002403700002402423700001902447700003502466700002002501700002202521700002202543700002202565700001902587700002402606700001502630700002202645700001602667700001902683700002402702700001802726700001902744700001902763700001802782700002102800700002202821700001702843700002102860700002302881700002102904700002202925700002002947700002502967700002002992700002503012700002103037700002603058700001803084700002003102700001803122700001903140700002003159700002003179700002103199700002203220700002603242700002303268700002103291700002403312700002803336700002403364700002503388700002803413700002803441700002303469700002403492700001903516700002003535700002203555700001703577700002103594700001603615700002003631700002303651700002303674700002003697700002303717700002203740700002403762700002203786700001603808700002103824700002603845700001703871700001903888700002403907700002003931700002203951700002203973700002003995700002404015700002104039700002204060700001904082700002304101700002504124700002804149700002104177700001904198700002004217856003604237 2011 eng d a1546-171800aGenetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile.0 aGenetic variation near IRS1 associates with reduced adiposity an c2011 Jun 26 a753-600 v433 aGenome-wide association studies have identified 32 loci influencing body mass index, but this measure does not distinguish lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ∼2.5 million SNPs and body fat percentage from 36,626 individuals and followed up the 14 most significant (P < 10(-6)) independent loci in 39,576 individuals. We confirmed a previously established adiposity locus in FTO (P = 3 × 10(-26)) and identified two new loci associated with body fat percentage, one near IRS1 (P = 4 × 10(-11)) and one near SPRY2 (P = 3 × 10(-8)). Both loci contain genes with potential links to adipocyte physiology. Notably, the body-fat-decreasing allele near IRS1 is associated with decreased IRS1 expression and with an impaired metabolic profile, including an increased visceral to subcutaneous fat ratio, insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.
10aAdiponectin10aAdiposity10aAlleles10aBody Fat Distribution10aBody Mass Index10aBody Weight10aFemale10aGenetic Variation10aGenome-Wide Association Study10aHumans10aInsulin Receptor Substrate Proteins10aIntracellular Signaling Peptides and Proteins10aMale10aMembrane Proteins10aMeta-Analysis as Topic10aMetabolome10aObesity10aPolymorphism, Single Nucleotide10aSubcutaneous Fat1 aKilpeläinen, Tuomas, O1 aZillikens, Carola, M1 aStančáková, Alena1 aFinucane, Francis, M1 aRied, Janina, S1 aLangenberg, Claudia1 aZhang, Weihua1 aBeckmann, Jacques, S1 aLuan, Jian'an1 aVandenput, Liesbeth1 aStyrkarsdottir, Unnur1 aZhou, Yanhua1 aSmith, Albert, Vernon1 aZhao, Jing-Hua1 aAmin, Najaf1 aVedantam, Sailaja1 aShin, So-Youn1 aHaritunians, Talin1 aFu, Mao1 aFeitosa, Mary, F1 aKumari, Meena1 aHalldorsson, Bjarni, V1 aTikkanen, Emmi1 aMangino, Massimo1 aHayward, Caroline1 aSong, Ci1 aArnold, Alice, M1 aAulchenko, Yurii, S1 aOostra, Ben, A1 aCampbell, Harry1 aCupples, Adrienne, L1 aDavis, Kathryn, E1 aDöring, Angela1 aEiriksdottir, Gudny1 aEstrada, Karol1 aFernández-Real, José, Manuel1 aGarcia, Melissa1 aGieger, Christian1 aGlazer, Nicole, L1 aGuiducci, Candace1 aHofman, Albert1 aHumphries, Steve, E1 aIsomaa, Bo1 aJacobs, Leonie, C1 aJula, Antti1 aKarasik, David1 aKarlsson, Magnus, K1 aKhaw, Kay-Tee1 aKim, Lauren, J1 aKivimaki, Mika1 aKlopp, Norman1 aKuhnel, Brigitte1 aKuusisto, Johanna1 aLiu, Yongmei1 aLjunggren, Osten1 aLorentzon, Mattias1 aLuben, Robert, N1 aMcKnight, Barbara1 aMellström, Dan1 aMitchell, Braxton, D1 aMooser, Vincent1 aMoreno, José, Maria1 aMännistö, Satu1 aO'Connell, Jeffery, R1 aPascoe, Laura1 aPeltonen, Leena1 aPeral, Belén1 aPerola, Markus1 aPsaty, Bruce, M1 aSalomaa, Veikko1 aSavage, David, B1 aSemple, Robert, K1 aSkaric-Juric, Tatjana1 aSigurdsson, Gunnar1 aSong, Kijoung, S1 aSpector, Timothy, D1 aSyvänen, Ann-Christine1 aTalmud, Philippa, J1 aThorleifsson, Gudmar1 aThorsteinsdottir, Unnur1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aVidal-Puig, Antonio1 aWild, Sarah, H1 aWright, Alan, F1 aClegg, Deborah, J1 aSchadt, Eric1 aWilson, James, F1 aRudan, Igor1 aRipatti, Samuli1 aBorecki, Ingrid, B1 aShuldiner, Alan, R1 aIngelsson, Erik1 aJansson, John-Olov1 aKaplan, Robert, C1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aGroop, Leif1 aKiel, Douglas, P1 aRivadeneira, Fernando1 aWalker, Mark1 aBarroso, Inês1 aVollenweider, Peter1 aWaeber, Gérard1 aChambers, John, C1 aKooner, Jaspal, S1 aSoranzo, Nicole1 aHirschhorn, Joel, N1 aStefansson, Kari1 aWichmann, H-Erich1 aOhlsson, Claes1 aO'Rahilly, Stephen1 aWareham, Nicholas, J1 aSpeliotes, Elizabeth, K1 aFox, Caroline, S1 aLaakso, Markku1 aLoos, Ruth, J F uhttps://chs-nhlbi.org/node/130103920nas a2200721 4500008004100000022001400041245017000055210006900225260001600294300001200310490000700322520181400329653001002143653002202153653000902175653001202184653001402196653001502210653004002225653001102265653001702276653003802293653003402331653001302365653000902378653001102387653002702398653000902425653001602434653003102450653003802481653003602519653001402555653001602569100001802585700002202603700002402625700001802649700001702667700002202684700002002706700001802726700002502744700002102769700002002790700001602810700002302826700002602849700002002875700001402895700002102909700002402930700002102954700002202975700002302997700002503020700002203045700002503067700002103092700001903113710003003132856003603162 2011 eng d a1460-208300aGenome-wide association study for serum urate concentrations and gout among African Americans identifies genomic risk loci and a novel URAT1 loss-of-function allele.0 aGenomewide association study for serum urate concentrations and c2011 Oct 15 a4056-680 v203 aSerum urate concentrations are highly heritable and elevated serum urate is a key risk factor for gout. Genome-wide association studies (GWAS) of serum urate in African American (AA) populations are lacking. We conducted a meta-analysis of GWAS of serum urate levels and gout among 5820 AA and a large candidate gene study among 6890 AA and 21 708 participants of European ancestry (EA) within the Candidate Gene Association Resource Consortium. Findings were tested for replication among 1996 independent AA individuals, and evaluated for their association among 28 283 EA participants of the CHARGE Consortium. Functional studies were conducted using (14)C-urate transport assays in mammalian Chinese hamster ovary cells. In the discovery GWAS of serum urate, three loci achieved genome-wide significance (P< 5.0 × 10(-8)): a novel locus near SGK1/SLC2A12 on chromosome 6 (rs9321453, P= 1.0 × 10(-9)), and two loci previously identified in EA participants, SLC2A9 (P= 3.8 × 10(-32)) and SLC22A12 (P= 2.1 × 10(-10)). A novel rare non-synonymous variant of large effect size in SLC22A12, rs12800450 (minor allele frequency 0.01, G65W), was identified and replicated (beta -1.19 mg/dl, P= 2.7 × 10(-16)). (14)C-urate transport assays showed reduced urate transport for the G65W URAT1 mutant. Finally, in analyses of 11 loci previously associated with serum urate in EA individuals, 10 of 11 lead single-nucleotide polymorphisms showed direction-consistent association with urate among AA. In summary, we identified and replicated one novel locus in association with serum urate levels and experimentally characterize the novel G65W variant in URAT1 as a functional allele. Our data support the importance of multi-ethnic GWAS in the identification of novel risk loci as well as functional variants.
10aAdult10aAfrican Americans10aAged10aAnimals10aCHO Cells10aCricetinae10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aGout10aHumans10aLoss of Heterozygosity10aMale10aMiddle Aged10aOrganic Anion Transporters10aOrganic Cation Transport Proteins10aPolymorphism, Single Nucleotide10aUric Acid10aYoung Adult1 aTin, Adrienne1 aWoodward, Owen, M1 aKao, Wen Hong Linda1 aLiu, Ching-Ti1 aLu, Xiaoning1 aNalls, Michael, A1 aShriner, Daniel1 aSemmo, Mariam1 aAkylbekova, Ermeg, L1 aWyatt, Sharon, B1 aHwang, Shih-Jen1 aYang, Qiong1 aZonderman, Alan, B1 aAdeyemo, Adebowale, A1 aPalmer, Cameron1 aMeng, Yan1 aReilly, Muredach1 aShlipak, Michael, G1 aSiscovick, David1 aEvans, Michele, K1 aRotimi, Charles, N1 aFlessner, Michael, F1 aKöttgen, Michael1 aCupples, Adrienne, L1 aFox, Caroline, S1 aKöttgen, Anna1 aCARe and CHARGE Consortia uhttps://chs-nhlbi.org/node/130504122nas a2201045 4500008004100000022001400041245014200055210006900197260001300266300001300279490000600292520107900298653001001377653000901387653001201396653003101408653002701439653004001466653001101506653001701517653003801534653003401572653001101606653000901617653001601626653002701642653003601669100001901705700002101724700002201745700002901767700002201796700002101818700002901839700002201868700002301890700002301913700002501936700002301961700002901984700002302013700002202036700001502058700001902073700002002092700002602112700001902138700003002157700002802187700002102215700001702236700002402253700002302277700001902300700002002319700002202339700001602361700001702377700002302394700001202417700001902429700001702448700002102465700001802486700002002504700002002524700002502544700002202569700002402591700001902615700002102634700002202655700002502677700001802702700001802720700002502738700002302763700002402786700003002810700002302840700001802863700002702881700001802908700002502926700002602951700001902977700002302996700002103019856003603040 2011 eng d a1553-740400aIdentification of a sudden cardiac death susceptibility locus at 2q24.2 through genome-wide association in European ancestry individuals.0 aIdentification of a sudden cardiac death susceptibility locus at c2011 Jun ae10021580 v73 aSudden cardiac death (SCD) continues to be one of the leading causes of mortality worldwide, with an annual incidence estimated at 250,000-300,000 in the United States and with the vast majority occurring in the setting of coronary disease. We performed a genome-wide association meta-analysis in 1,283 SCD cases and >20,000 control individuals of European ancestry from 5 studies, with follow-up genotyping in up to 3,119 SCD cases and 11,146 controls from 11 European ancestry studies, and identify the BAZ2B locus as associated with SCD (P = 1.8×10(-10)). The risk allele, while ancestral, has a frequency of ~1.4%, suggesting strong negative selection and increases risk for SCD by 1.92-fold per allele (95% CI 1.57-2.34). We also tested the role of 49 SNPs previously implicated in modulating electrocardiographic traits (QRS, QT, and RR intervals). Consistent with epidemiological studies showing increased risk of SCD with prolonged QRS/QT intervals, the interval-prolonging alleles are in aggregate associated with increased risk for SCD (P = 0.006).
10aAdult10aAged10aAlleles10aChromosomes, Human, Pair 210aDeath, Sudden, Cardiac10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aMyocardial Contraction10aPolymorphism, Single Nucleotide1 aArking, Dan, E1 aJunttila, Juhani1 aGoyette, Philippe1 aHuertas-Vazquez, Adriana1 aEijgelsheim, Mark1 aBlom, Marieke, T1 aNewton-Cheh, Christopher1 aReinier, Kyndaron1 aTeodorescu, Carmen1 aUy-Evanado, Audrey1 aCarter-Monroe, Naima1 aKaikkonen, Kari, S1 aKortelainen, Marja-Leena1 aBoucher, Gabrielle1 aLagacé, Caroline1 aMoes, Anna1 aZhao, XiaoQing1 aKolodgie, Frank1 aRivadeneira, Fernando1 aHofman, Albert1 aWitteman, Jacqueline, C M1 aUitterlinden, André, G1 aMarsman, Roos, F1 aPazoki, Raha1 aBardai, Abdennasser1 aKoster, Rudolph, W1 aDehghan, Abbas1 aHwang, Shih-Jen1 aBhatnagar, Pallav1 aPost, Wendy1 aHilton, Gina1 aPrineas, Ronald, J1 aLi, Man1 aKöttgen, Anna1 aEhret, Georg1 aBoerwinkle, Eric1 aCoresh, Josef1 aKao, Linda, W H1 aPsaty, Bruce, M1 aTomaselli, Gordon, F1 aSotoodehnia, Nona1 aSiscovick, David, S1 aBurke, Greg, L1 aMarbán, Eduardo1 aSpooner, Peter, M1 aCupples, Adrienne, L1 aJui, Jonathan1 aGunson, Karen1 aKesaniemi, Antero, Y1 aWilde, Arthur, A M1 aTardif, Jean-Claude1 aO'Donnell, Christopher, J1 aBezzina, Connie, R1 aVirmani, Renu1 aStricker, Bruno, H C H1 aTan, Hanno, L1 aAlbert, Christine, M1 aChakravarti, Aravinda1 aRioux, John, D1 aHuikuri, Heikki, V1 aChugh, Sumeet, S uhttps://chs-nhlbi.org/node/130403188nas a2200553 4500008004100000022001400041245012300055210006900178260001300247300000900260490000700269520163300276653001001909653000901919653002001928653002501948653003001973653001602003653001202019653001102031653001802042653003402060653001302094653001102107653001202118653002702130653000902157653002702166653002702193653001602220653003602236653001502272100002202287700002202309700001802331700001802349700001302367700001702380700001902397700002802416700002202444700002502466700002302491700002002514700002002534700002502554700001902579856003602598 2011 eng d a1098-227200aMeta-analysis of gene-environment interaction: joint estimation of SNP and SNP × environment regression coefficients.0 aMetaanalysis of geneenvironment interaction joint estimation of c2011 Jan a11-80 v353 aINTRODUCTION: Genetic discoveries are validated through the meta-analysis of genome-wide association scans in large international consortia. Because environmental variables may interact with genetic factors, investigation of differing genetic effects for distinct levels of an environmental exposure in these large consortia may yield additional susceptibility loci undetected by main effects analysis. We describe a method of joint meta-analysis (JMA) of SNP and SNP by Environment (SNP × E) regression coefficients for use in gene-environment interaction studies.
METHODS: In testing SNP × E interactions, one approach uses a two degree of freedom test to identify genetic variants that influence the trait of interest. This approach detects both main and interaction effects between the trait and the SNP. We propose a method to jointly meta-analyze the SNP and SNP × E coefficients using multivariate generalized least squares. This approach provides confidence intervals of the two estimates, a joint significance test for SNP and SNP × E terms, and a test of homogeneity across samples.
RESULTS: We present a simulation study comparing this method to four other methods of meta-analysis and demonstrate that the JMA performs better than the others when both main and interaction effects are present. Additionally, we implemented our methods in a meta-analysis of the association between SNPs from the type 2 diabetes-associated gene PPARG and log-transformed fasting insulin levels and interaction by body mass index in a combined sample of 19,466 individuals from five cohorts.
10aAdult10aAged10aBody Mass Index10aConfidence Intervals10aDiabetes Mellitus, Type 210aEnvironment10aFasting10aFemale10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHumans10aInsulin10aLeast-Squares Analysis10aMale10aMathematical Computing10aMeta-Analysis as Topic10aMiddle Aged10aPolymorphism, Single Nucleotide10aPPAR gamma1 aManning, Alisa, K1 aLaValley, Michael1 aLiu, Ching-Ti1 aRice, Kenneth1 aAn, Ping1 aLiu, Yongmei1 aMiljkovic, Iva1 aRasmussen-Torvik, Laura1 aHarris, Tamara, B1 aProvince, Michael, A1 aBorecki, Ingrid, B1 aFlorez, Jose, C1 aMeigs, James, B1 aCupples, Adrienne, L1 aDupuis, Josée uhttps://chs-nhlbi.org/node/125805459nas a2201501 4500008004100000022001400041245016600055210006900221260001600290300001000306490000700316520120500323653001001528653000901538653001001547653002001557653003501577653001901612653002801631653004001659653001701699653003801716653001801754653003401772653001301806653001001819653001101829653001601840653001401856653002801870653003601898653001701934100001901951700002001970700002301990700001802013700002502031700001802056700001902074700002102093700002502114700002002139700002202159700002502181700002202206700001802228700002002246700002302266700001902289700001602308700001602324700001702340700002502357700002202382700002002404700002302424700002002447700001802467700001902485700002002504700002002524700002102544700001802565700002602583700001702609700001902626700002302645700002002668700002302688700002402711700001802735700001802753700001902771700002302790700002202813700002402835700001702859700002402876700002102900700002102921700002002942700001802962700002102980700001703001700001903018700002303037700002403060700002203084700002203106700001903128700002103147700001803168700002003186700001903206700002203225700002503247700002303272700002503295700002003320700002103340700002303361700002703384700002203411700002003433700002003453700002103473700001203494700002303506700001703529700002103546700001803567700002003585700002103605700001903626700002103645700002403666700002003690700002503710700001903735700002403754700002003778700001803798700002503816700002403841700003003865710002603895856003603921 2011 eng d a1546-171800aMeta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque.0 aMetaanalysis of genomewide association studies from the CHARGE c c2011 Sep 11 a940-70 v433 aCarotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10(-8)). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events.
10aAdult10aAged10aAging10aAtherosclerosis10aCarotid Intima-Media Thickness10aCohort Studies10aCoronary Artery Disease10aEuropean Continental Ancestry Group10aGenetic Loci10aGenetic Predisposition to Disease10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHeart10aHumans10aMiddle Aged10aPhenotype10aPlaque, Atherosclerotic10aPolymorphism, Single Nucleotide10aRisk Factors1 aBis, Joshua, C1 aKavousi, Maryam1 aFranceschini, Nora1 aIsaacs, Aaron1 aAbecasis, Goncalo, R1 aSchminke, Ulf1 aPost, Wendy, S1 aSmith, Albert, V1 aCupples, Adrienne, L1 aMarkus, Hugh, S1 aSchmidt, Reinhold1 aHuffman, Jennifer, E1 aLehtimäki, Terho1 aBaumert, Jens1 aMünzel, Thomas1 aHeckbert, Susan, R1 aDehghan, Abbas1 aNorth, Kari1 aOostra, Ben1 aBevan, Steve1 aStoegerer, Eva-Maria1 aHayward, Caroline1 aRaitakari, Olli1 aMeisinger, Christa1 aSchillert, Arne1 aSanna, Serena1 aVölzke, Henry1 aCheng, Yu-Ching1 aThorsson, Bolli1 aFox, Caroline, S1 aRice, Kenneth1 aRivadeneira, Fernando1 aNambi, Vijay1 aHalperin, Eran1 aPetrovic, Katja, E1 aPeltonen, Leena1 aWichmann, Erich, H1 aSchnabel, Renate, B1 aDörr, Marcus1 aParsa, Afshin1 aAspelund, Thor1 aDemissie, Serkalem1 aKathiresan, Sekar1 aReilly, Muredach, P1 aTaylor, Kent1 aUitterlinden, Andre1 aCouper, David, J1 aSitzer, Matthias1 aKähönen, Mika1 aIllig, Thomas1 aWild, Philipp, S1 aOrrù, Marco1 aLüdemann, Jan1 aShuldiner, Alan, R1 aEiriksdottir, Gudny1 aWhite, Charles, C1 aRotter, Jerome, I1 aHofman, Albert1 aSeissler, Jochen1 aZeller, Tanja1 aUsala, Gianluca1 aErnst, Florian1 aLauner, Lenore, J1 aD'Agostino, Ralph, B1 aO'Leary, Daniel, H1 aBallantyne, Christie1 aThiery, Joachim1 aZiegler, Andreas1 aLakatta, Edward, G1 aChilukoti, Ravi, Kumar1 aHarris, Tamara, B1 aWolf, Philip, A1 aPsaty, Bruce, M1 aPolak, Joseph, F1 aLi, Xia1 aRathmann, Wolfgang1 aUda, Manuela1 aBoerwinkle, Eric1 aKlopp, Norman1 aSchmidt, Helena1 aWilson, James, F1 aViikari, Jorma1 aKoenig, Wolfgang1 aBlankenberg, Stefan1 aNewman, Anne, B1 aWitteman, Jacqueline1 aHeiss, Gerardo1 avan Duijn, Cornelia1 aScuteri, Angelo1 aHomuth, Georg1 aMitchell, Braxton, D1 aGudnason, Vilmundur1 aO'Donnell, Christopher, J1 aCARDIoGRAM consortium uhttps://chs-nhlbi.org/node/132304525nas a2200901 4500008004100000022001400041245012800055210006900183260001300252300001200265490000700277520189900284653001802183653003002201653001902231653001102250653003602261653000902297653002302306100002202329700002702351700002502378700001402403700002602417700002002443700002102463700002002484700002402504700002402528700002302552700002602575700002002601700001802621700002002639700002002659700002302679700002302702700002002725700002102745700001902766700002202785700002302807700001702830700002102847700002402868700001502892700001702907700002002924700001802944700002102962700002502983700002803008700002803036700002203064700002503086700002103111700002103132700002503153700002103178700002503199700001803224700002103242700001903263700002403282700002003306700002803326700002203354700002003376700002303396700003003419700002503449700002403474700002003498700002003518700002503538710002403563856003603587 2011 eng d a1939-327X00aTotal zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis.0 aTotal zinc intake may modify the glucoseraising effect of a zinc c2011 Sep a2407-160 v603 aOBJECTIVE: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants.
RESEARCH DESIGN AND METHODS: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes.
RESULTS: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: -0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant.
CONCLUSIONS: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.
10aBlood Glucose10aCation Transport Proteins10aCohort Studies10aHumans10aPolymorphism, Single Nucleotide10aZinc10aZinc Transporter 81 aKanoni, Stavroula1 aNettleton, Jennifer, A1 aHivert, Marie-France1 aYe, Zheng1 avan Rooij, Frank, J A1 aShungin, Dmitry1 aSonestedt, Emily1 aNgwa, Julius, S1 aWojczynski, Mary, K1 aLemaitre, Rozenn, N1 aGustafsson, Stefan1 aAnderson, Jennifer, S1 aTanaka, Toshiko1 aHindy, George1 aSaylor, Georgia1 aRenstrom, Frida1 aBennett, Amanda, J1 aDuijn, Cornelia, M1 aFlorez, Jose, C1 aFox, Caroline, S1 aHofman, Albert1 aHoogeveen, Ron, C1 aHouston, Denise, K1 aHu, Frank, B1 aJacques, Paul, F1 aJohansson, Ingegerd1 aLind, Lars1 aLiu, Yongmei1 aMcKeown, Nicola1 aOrdovas, Jose1 aPankow, James, S1 aSijbrands, Eric, J G1 aSyvänen, Ann-Christine1 aUitterlinden, André, G1 aYannakoulia, Mary1 aZillikens, Carola, M1 aWareham, Nick, J1 aProkopenko, Inga1 aBandinelli, Stefania1 aForouhi, Nita, G1 aCupples, Adrienne, L1 aLoos, Ruth, J1 aHallmans, Göran1 aDupuis, Josée1 aLangenberg, Claudia1 aFerrucci, Luigi1 aKritchevsky, Stephen, B1 aMcCarthy, Mark, I1 aIngelsson, Erik1 aBorecki, Ingrid, B1 aWitteman, Jacqueline, C M1 aOrho-Melander, Marju1 aSiscovick, David, S1 aMeigs, James, B1 aFranks, Paul, W1 aDedoussis, George, V1 aMAGIC investigators uhttps://chs-nhlbi.org/node/130805540nas a2201357 4500008004100000022001400041245007400055210006900129260001300198300001200211490000700223520169700230653001701927653001901944653001101963653001001974653003401984653001102018653000902029653002702038653003602065653002802101653003102129653002402160100001802184700001902202700003102221700001602252700002502268700001202293700002102305700002402326700002502350700001402375700001702389700001802406700001802424700001902442700002802461700001902489700002502508700002402533700002302557700002502580700002102605700001602626700002602642700001902668700002102687700001902708700002002727700002102747700002102768700002402789700001702813700002002830700001302850700002102863700002502884700001802909700002002927700003002947700002102977700002702998700002203025700002903047700002103076700002303097700001603120700002003136700001903156700002003175700002303195700002203218700002403240700002003264700001703284700002703301700003103328700002303359700002003382700002103402700001503423700002803438700001903466700002303485700002503508700002403533700001903557700001903576700001703595700002503612700002603637700001903663700002203682700002103704700002703725700002603752700002803778700002503806700002403831700002003855700002203875700002403897700002003921700002103941700002503962700002603987700002304013700001904036700002604055700002104081700002504102700001904127856003604146 2012 eng d a1523-468100aAssessment of gene-by-sex interaction effect on bone mineral density.0 aAssessment of genebysex interaction effect on bone mineral densi c2012 Oct a2051-640 v273 aSexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 × 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 × 10(-5) ; female effect = -0.007 and p = 3.3 × 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 × 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. © 2012 American Society for Bone and Mineral Research.
10aBone Density10aCohort Studies10aFemale10aGenes10aGenome-Wide Association Study10aHumans10aMale10aMeta-Analysis as Topic10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aReproducibility of Results10aSex Characteristics1 aLiu, Ching-Ti1 aEstrada, Karol1 aYerges-Armstrong, Laura, M1 aAmin, Najaf1 aEvangelou, Evangelos1 aLi, Guo1 aMinster, Ryan, L1 aCarless, Melanie, A1 aKammerer, Candace, M1 aOei, Ling1 aZhou, Yanhua1 aAlonso, Nerea1 aDailiana, Zoe1 aEriksson, Joel1 aGarcía-Giralt, Natalia1 aGiroux, Sylvie1 aHusted, Lise, Bjerre1 aKhusainova, Rita, I1 aKoromila, Theodora1 aKung, Annie, Waichee1 aLewis, Joshua, R1 aMasi, Laura1 aMencej-Bedrac, Simona1 aNogues, Xavier1 aPatel, Millan, S1 aPrezelj, Janez1 aRichards, Brent1 aSham, Pak, Chung1 aSpector, Timothy1 aVandenput, Liesbeth1 aXiao, Su-Mei1 aZheng, Hou-Feng1 aZhu, Kun1 aBalcells, Susana1 aBrandi, Maria, Luisa1 aFrost, Morten1 aGoltzman, David1 aGonzález-Macías, Jesús1 aKarlsson, Magnus1 aKhusnutdinova, Elza, K1 aKollia, Panagoula1 aLangdahl, Bente, Lomholt1 aLjunggren, Osten1 aLorentzon, Mattias1 aMarc, Janja1 aMellström, Dan1 aOhlsson, Claes1 aOlmos, José, M1 aRalston, Stuart, H1 aRiancho, José, A1 aRousseau, François1 aUrreizti, Roser1 aVan Hul, Wim1 aZarrabeitia, María, T1 aCastano-Betancourt, Martha1 aDemissie, Serkalem1 aGrundberg, Elin1 aHerrera, Lizbeth1 aKwan, Tony1 aMedina-Gómez, Carolina1 aPastinen, Tomi1 aSigurdsson, Gunnar1 aThorleifsson, Gudmar1 aVanmeurs, Joyce, Bj1 aBlangero, John1 aHofman, Albert1 aLiu, Yongmei1 aMitchell, Braxton, D1 aO'Connell, Jeffrey, R1 aOostra, Ben, A1 aRotter, Jerome, I1 aStefansson, Kari1 aStreeten, Elizabeth, A1 aStyrkarsdottir, Unnur1 aThorsteinsdottir, Unnur1 aTylavsky, Frances, A1 aUitterlinden, Andre1 aCauley, Jane, A1 aHarris, Tamara, B1 aIoannidis, John, Pa1 aPsaty, Bruce, M1 aRobbins, John, A1 aZillikens, Carola, M1 aVanduijn, Cornelia, M1 aPrince, Richard, L1 aKarasik, David1 aRivadeneira, Fernando1 aKiel, Douglas, P1 aCupples, Adrienne, L1 aHsu, Yi-Hsiang uhttps://chs-nhlbi.org/node/155607377nas a2201945 4500008004100000022001400041245014700055210006900202260001600271300001100287490000600298520192200304653001002226653001602236653000902252653002202261653001202283653002502295653003102320653001902351653004202370653001102412653003402423653001302457653001902470653001102489653002002500653000902520653001602529653003302545653001402578653003602592653001702628653001602645100002402661700002202685700002002707700001602727700002102743700001702764700002002781700002002801700002002821700001902841700001702860700002202877700002302899700002502922700001702947700002202964700002502986700002003011700001903031700002303050700002203073700001903095700002103114700001803135700002203153700001503175700002203190700002203212700002003234700002503254700002103279700002403300700001603324700001803340700002703358700002103385700002503406700001903431700001803450700002603468700002103494700002303515700001903538700002403557700002503581700002003606700001803626700003003644700002203674700002003696700002103716700002203737700001903759700002003778700001803798700002403816700001903840700001903859700001803878700002703896700001803923700002303941700002803964700002103992700001604013700001904029700001704048700002304065700001804088700002104106700001804127700002004145700001804165700002904183700002104212700002004233700003004253700001904283700002304302700002304325700001904348700002004367700002104387700001404408700002604422700002204448700002204470700002204492700002104514700002004535700002604555700002804581700001904609700002304628700001904651700002104670700002004691700001804711700002204729700001604751700002904767700002404796700002104820700002004841700001904861700002504880700002204905700002404927700002504951700001704976700002004993700002005013700001905033700001605052700002305068700002005091700002305111700001705134700002005151700002205171700002105193700003005214700001705244700002205261700002305283700002105306700001905327700002505346700002405371856003605395 2012 eng d a1942-326800aAssociation between chromosome 9p21 variants and the ankle-brachial index identified by a meta-analysis of 21 genome-wide association studies.0 aAssociation between chromosome 9p21 variants and the anklebrachi c2012 Feb 01 a100-120 v53 aBACKGROUND: Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts.
METHODS AND RESULTS: Continuous ABI and PAD (ABI ≤0.9) phenotypes adjusted for age and sex were examined. Each study conducted genotyping and imputed data to the ≈2.5 million single nucleotide polymorphisms (SNPs) in HapMap. Linear and logistic regression models were used to test each SNP for association with ABI and PAD using additive genetic models. Study-specific data were combined using fixed effects inverse variance weighted meta-analyses. There were a total of 41 692 participants of European ancestry (≈60% women, mean ABI 1.02 to 1.19), including 3409 participants with PAD and with genome-wide association study data available. In the discovery meta-analysis, rs10757269 on chromosome 9 near CDKN2B had the strongest association with ABI (β=-0.006, P=2.46×10(-8)). We sought replication of the 6 strongest SNP associations in 5 population-based studies and 3 clinical samples (n=16 717). The association for rs10757269 strengthened in the combined discovery and replication analysis (P=2.65×10(-9)). No other SNP associations for ABI or PAD achieved genome-wide significance. However, 2 previously reported candidate genes for PAD and 1 SNP associated with coronary artery disease were associated with ABI: DAB21P (rs13290547, P=3.6×10(-5)), CYBA (rs3794624, P=6.3×10(-5)), and rs1122608 (LDLR, P=0.0026).
CONCLUSIONS: Genome-wide association studies in more than 40 000 individuals identified 1 genome wide significant association on chromosome 9p21 with ABI. Two candidate genes for PAD and 1 SNP for coronary artery disease are associated with ABI.
10aAdult10aAge Factors10aAged10aAged, 80 and over10aAlleles10aAnkle Brachial Index10aChromosomes, Human, Pair 910aCohort Studies10aCyclin-Dependent Kinase Inhibitor p1510aFemale10aGenome-Wide Association Study10aGenotype10aHapMap Project10aHumans10aLogistic Models10aMale10aMiddle Aged10aPeripheral Vascular Diseases10aPhenotype10aPolymorphism, Single Nucleotide10aRisk Factors10aSex Factors1 aMurabito, Joanne, M1 aWhite, Charles, C1 aKavousi, Maryam1 aSun, Yan, V1 aFeitosa, Mary, F1 aNambi, Vijay1 aLamina, Claudia1 aSchillert, Arne1 aCoassin, Stefan1 aBis, Joshua, C1 aBroer, Linda1 aCrawford, Dana, C1 aFranceschini, Nora1 aFrikke-Schmidt, Ruth1 aHaun, Margot1 aHolewijn, Suzanne1 aHuffman, Jennifer, E1 aHwang, Shih-Jen1 aKiechl, Stefan1 aKollerits, Barbara1 aMontasser, May, E1 aNolte, Ilja, M1 aRudock, Megan, E1 aSenft, Andrea1 aTeumer, Alexander1 aHarst, Pim1 aVitart, Veronique1 aWaite, Lindsay, L1 aWood, Andrew, R1 aWassel, Christina, L1 aAbsher, Devin, M1 aAllison, Matthew, A1 aAmin, Najaf1 aArnold, Alice1 aAsselbergs, Folkert, W1 aAulchenko, Yurii1 aBandinelli, Stefania1 aBarbalic, Maja1 aBoban, Mladen1 aBrown-Gentry, Kristin1 aCouper, David, J1 aCriqui, Michael, H1 aDehghan, Abbas1 aHeijer, Martin, den1 aDieplinger, Benjamin1 aDing, Jingzhong1 aDörr, Marcus1 aEspinola-Klein, Christine1 aFelix, Stephan, B1 aFerrucci, Luigi1 aFolsom, Aaron, R1 aFraedrich, Gustav1 aGibson, Quince1 aGoodloe, Robert1 aGunjaca, Grgo1 aHaltmayer, Meinhard1 aHeiss, Gerardo1 aHofman, Albert1 aKieback, Arne1 aKiemeney, Lambertus, A1 aKolcic, Ivana1 aKullo, Iftikhar, J1 aKritchevsky, Stephen, B1 aLackner, Karl, J1 aLi, Xiaohui1 aLieb, Wolfgang1 aLohman, Kurt1 aMeisinger, Christa1 aMelzer, David1 aMohler, Emile, R1 aMudnic, Ivana1 aMueller, Thomas1 aNavis, Gerjan1 aOberhollenzer, Friedrich1 aOlin, Jeffrey, W1 aO'Connell, Jeff1 aO'Donnell, Christopher, J1 aPalmas, Walter1 aPenninx, Brenda, W1 aPetersmann, Astrid1 aPolasek, Ozren1 aPsaty, Bruce, M1 aRantner, Barbara1 aRice, Ken1 aRivadeneira, Fernando1 aRotter, Jerome, I1 aSeldenrijk, Adrie1 aStadler, Marietta1 aSummerer, Monika1 aTanaka, Toshiko1 aTybjaerg-Hansen, Anne1 aUitterlinden, André, G1 aGilst, Wiek, H1 aVermeulen, Sita, H1 aWild, Sarah, H1 aWild, Philipp, S1 aWilleit, Johann1 aZeller, Tanja1 aZemunik, Tatijana1 aZgaga, Lina1 aAssimes, Themistocles, L1 aBlankenberg, Stefan1 aBoerwinkle, Eric1 aCampbell, Harry1 aCooke, John, P1 ade Graaf, Jacqueline1 aHerrington, David1 aKardia, Sharon, L R1 aMitchell, Braxton, D1 aMurray, Anna1 aMünzel, Thomas1 aNewman, Anne, B1 aOostra, Ben, A1 aRudan, Igor1 aShuldiner, Alan, R1 aSnieder, Harold1 aDuijn, Cornelia, M1 aVölker, Uwe1 aWright, Alan, F1 aWichmann, H-Erich1 aWilson, James, F1 aWitteman, Jacqueline, C M1 aLiu, Yongmei1 aHayward, Caroline1 aBorecki, Ingrid, B1 aZiegler, Andreas1 aNorth, Kari, E1 aCupples, Adrienne, L1 aKronenberg, Florian uhttps://chs-nhlbi.org/node/135908598nas a2202365 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2012 eng d a1476-468700aFTO genotype is associated with phenotypic variability of body mass index.0 aFTO genotype is associated with phenotypic variability of body m c2012 Oct 11 a267-720 v4903 aThere is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
10aAlpha-Ketoglutarate-Dependent Dioxygenase FTO10aBody Height10aBody Mass Index10aCo-Repressor Proteins10aFemale10aGenetic Variation10aGenome-Wide Association Study10aHumans10aMale10aNerve Tissue Proteins10aPhenotype10aPolymorphism, Single Nucleotide10aProteins10aRepressor Proteins1 aYang, Jian1 aLoos, Ruth, J F1 aPowell, Joseph, E1 aMedland, Sarah, E1 aSpeliotes, Elizabeth, K1 aChasman, Daniel, I1 aRose, Lynda, M1 aThorleifsson, Gudmar1 aSteinthorsdottir, Valgerdur1 aMägi, Reedik1 aWaite, Lindsay1 aSmith, Albert, Vernon1 aYerges-Armstrong, Laura, M1 aMonda, Keri, L1 aHadley, David1 aMahajan, Anubha1 aLi, Guo1 aKapur, Karen1 aVitart, Veronique1 aHuffman, Jennifer, E1 aWang, Sophie, R1 aPalmer, Cameron1 aEsko, Tõnu1 aFischer, Krista1 aZhao, Jing Hua1 aDemirkan, Ayse1 aIsaacs, Aaron1 aFeitosa, Mary, F1 aLuan, Jian'an1 aHeard-Costa, Nancy, L1 aWhite, Charles1 aJackson, Anne, U1 aPreuss, Michael1 aZiegler, Andreas1 aEriksson, Joel1 aKutalik, Zoltán1 aFrau, Francesca1 aNolte, Ilja, M1 avan Vliet-Ostaptchouk, Jana, V1 aHottenga, Jouke-Jan1 aJacobs, Kevin, B1 aVerweij, Niek1 aGoel, Anuj1 aMedina-Gómez, Carolina1 aEstrada, Karol1 aBragg-Gresham, Jennifer, Lynn1 aSanna, Serena1 aSidore, Carlo1 aTyrer, Jonathan1 aTeumer, Alexander1 aProkopenko, Inga1 aMangino, Massimo1 aLindgren, Cecilia, M1 aAssimes, Themistocles, L1 aShuldiner, Alan, R1 aHui, Jennie1 aBeilby, John, P1 aMcArdle, Wendy, L1 aHall, Per1 aHaritunians, Talin1 aZgaga, Lina1 aKolcic, Ivana1 aPolasek, Ozren1 aZemunik, Tatijana1 aOostra, Ben, A1 aJunttila, Juhani1 aGrönberg, Henrik1 aSchreiber, Stefan1 aPeters, Annette1 aHicks, Andrew, A1 aStephens, Jonathan1 aFoad, Nicola, S1 aLaitinen, Jaana1 aPouta, Anneli1 aKaakinen, Marika1 aWillemsen, Gonneke1 aVink, Jacqueline, M1 aWild, Sarah, H1 aNavis, Gerjan1 aAsselbergs, Folkert, W1 aHomuth, Georg1 aJohn, Ulrich1 aIribarren, Carlos1 aHarris, Tamara1 aLauner, Lenore1 aGudnason, Vilmundur1 aO'Connell, Jeffrey, R1 aBoerwinkle, Eric1 aCadby, Gemma1 aPalmer, Lyle, J1 aJames, Alan, L1 aMusk, Arthur, W1 aIngelsson, Erik1 aPsaty, Bruce, M1 aBeckmann, Jacques, S1 aWaeber, Gérard1 aVollenweider, Peter1 aHayward, Caroline1 aWright, Alan, F1 aRudan, Igor1 aGroop, Leif, C1 aMetspalu, Andres1 aKhaw, Kay, Tee1 aDuijn, Cornelia, M1 aBorecki, Ingrid, B1 aProvince, Michael, A1 aWareham, Nicholas, J1 aTardif, Jean-Claude1 aHuikuri, Heikki, V1 aCupples, Adrienne, L1 aAtwood, Larry, D1 aFox, Caroline, S1 aBoehnke, Michael1 aCollins, Francis, S1 aMohlke, Karen, L1 aErdmann, Jeanette1 aSchunkert, Heribert1 aHengstenberg, Christian1 aStark, Klaus1 aLorentzon, Mattias1 aOhlsson, Claes1 aCusi, Daniele1 aStaessen, Jan, A1 avan der Klauw, Melanie, M1 aPramstaller, Peter, P1 aKathiresan, Sekar1 aJolley, Jennifer, D1 aRipatti, Samuli1 aJarvelin, Marjo-Riitta1 aGeus, Eco, J C1 aBoomsma, Dorret, I1 aPenninx, Brenda1 aWilson, James, F1 aCampbell, Harry1 aChanock, Stephen, J1 aHarst, Pim1 aHamsten, Anders1 aWatkins, Hugh1 aHofman, Albert1 aWitteman, Jacqueline, C1 aZillikens, Carola, M1 aUitterlinden, André, G1 aRivadeneira, Fernando1 aZillikens, Carola, M1 aKiemeney, Lambertus, A1 aVermeulen, Sita, H1 aAbecasis, Goncalo, R1 aSchlessinger, David1 aSchipf, Sabine1 aStumvoll, Michael1 aTönjes, Anke1 aSpector, Tim, D1 aNorth, Kari, E1 aLettre, Guillaume1 aMcCarthy, Mark, I1 aBerndt, Sonja, I1 aHeath, Andrew, C1 aMadden, Pamela, A F1 aNyholt, Dale, R1 aMontgomery, Grant, W1 aMartin, Nicholas, G1 aMcKnight, Barbara1 aStrachan, David, P1 aHill, William, G1 aSnieder, Harold1 aRidker, Paul, M1 aThorsteinsdottir, Unnur1 aStefansson, Kari1 aFrayling, Timothy, M1 aHirschhorn, Joel, N1 aGoddard, Michael, E1 aVisscher, Peter, M uhttps://chs-nhlbi.org/node/617505476nas a2201057 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2012 eng d a1879-148400aGenetic determinants of the ankle-brachial index: a meta-analysis of a cardiovascular candidate gene 50K SNP panel in the candidate gene association resource (CARe) consortium.0 aGenetic determinants of the anklebrachial index a metaanalysis o c2012 May a138-470 v2223 aBACKGROUND: Candidate gene association studies for peripheral artery disease (PAD), including subclinical disease assessed with the ankle-brachial index (ABI), have been limited by the modest number of genes examined. We conducted a two stage meta-analysis of ∼50,000 SNPs across ∼2100 candidate genes to identify genetic variants for ABI.
METHODS AND RESULTS: We studied subjects of European ancestry from 8 studies (n=21,547, 55% women, mean age 44-73 years) and African American ancestry from 5 studies (n=7267, 60% women, mean age 41-73 years) involved in the candidate gene association resource (CARe) consortium. In each ethnic group, additive genetic models were used (with each additional copy of the minor allele corresponding to the given beta) to test each SNP for association with continuous ABI (excluding ABI>1.40) and PAD (defined as ABI<0.90) using linear or logistic regression with adjustment for known PAD risk factors and population stratification. We then conducted a fixed-effects inverse-variance weighted meta-analyses considering a p<2×10(-6) to denote statistical significance.
RESULTS: In the European ancestry discovery meta-analyses, rs2171209 in SYTL3 (β=-0.007, p=6.02×10(-7)) and rs290481 in TCF7L2 (β=-0.008, p=7.01×10(-7)) were significantly associated with ABI. None of the SNP associations for PAD were significant, though a SNP in CYP2B6 (p=4.99×10(-5)) was among the strongest associations. These 3 genes are linked to key PAD risk factors (lipoprotein(a), type 2 diabetes, and smoking behavior, respectively). We sought replication in 6 population-based and 3 clinical samples (n=15,440) for rs290481 and rs2171209. However, in the replication stage (rs2171209, p=0.75; rs290481, p=0.19) and in the combined discovery and replication analysis the SNP-ABI associations were no longer significant (rs2171209, p=1.14×10(-3); rs290481, p=8.88×10(-5)). In African Americans, none of the SNP associations for ABI or PAD achieved an experiment-wide level of significance.
CONCLUSIONS: Genetic determinants of ABI and PAD remain elusive. Follow-up of these preliminary findings may uncover important biology given the known gene-risk factor associations. New and more powerful approaches to PAD gene discovery are warranted.
10aAdult10aAfrican Americans10aAged10aAnkle Brachial Index10aAryl Hydrocarbon Hydroxylases10aCytochrome P-450 CYP2B610aEuropean Continental Ancestry Group10aFemale10aHumans10aMale10aMiddle Aged10aOxidoreductases, N-Demethylating10aPeripheral Arterial Disease10aPolymorphism, Single Nucleotide10aRisk Factors10aTranscription Factor 7-Like 2 Protein1 aWassel, Christina, L1 aLamina, Claudia1 aNambi, Vijay1 aCoassin, Stefan1 aMukamal, Kenneth, J1 aGanesh, Santhi, K1 aJacobs, David, R1 aFranceschini, Nora1 aPapanicolaou, George, J1 aGibson, Quince1 aYanek, Lisa, R1 aHarst, Pim1 aFerguson, Jane, F1 aCrawford, Dana, C1 aWaite, Lindsay, L1 aAllison, Matthew, A1 aCriqui, Michael, H1 aMcDermott, Mary, M1 aMehra, Reena1 aCupples, Adrienne, L1 aHwang, Shih-Jen1 aRedline, Susan1 aKaplan, Robert, C1 aHeiss, Gerardo1 aRotter, Jerome, I1 aBoerwinkle, Eric1 aTaylor, Herman, A1 aEraso, Luis, H1 aHaun, Margot1 aLi, Mingyao1 aMeisinger, Christa1 aO'Connell, Jeffrey, R1 aShuldiner, Alan, R1 aTybjærg-Hansen, Anne1 aFrikke-Schmidt, Ruth1 aKollerits, Barbara1 aRantner, Barbara1 aDieplinger, Benjamin1 aStadler, Marietta1 aMueller, Thomas1 aHaltmayer, Meinhard1 aKlein-Weigel, Peter1 aSummerer, Monika1 aWichmann, H-Erich1 aAsselbergs, Folkert, W1 aNavis, Gerjan1 aLeach, Irene, Mateo1 aBrown-Gentry, Kristin1 aGoodloe, Robert1 aAssimes, Themistocles, L1 aBecker, Diane, M1 aCooke, John, P1 aAbsher, Devin, M1 aOlin, Jeffrey, W1 aMitchell, Braxton, D1 aReilly, Muredach, P1 aMohler, Emile, R1 aNorth, Kari, E1 aReiner, Alexander, P1 aKronenberg, Florian1 aMurabito, Joanne, M uhttps://chs-nhlbi.org/node/586408678nas a2202593 4500008004100000022001400041245012400055210006900179260001600248300001200264490000700276520126400283653001701547653002601564653004001590653003401630653001101664653001501675653002001690653003001710653003801740653003401778653001301812653001801825653001101843653005001854653005501904653002101959653000901980653004601989653001702035653002002052653003602072653002802108653001702136653001302153100001902166700002602185700002502211700001902236700002002255700002502275700001402300700002302314700001602337700001802353700002202371700001202393700001802405700002102423700002202444700002402466700001802490700001702508700003102525700002002556700001802576700001902594700002502613700002402638700001702662700002502679700002102704700002102725700001702746700001702763700002202780700001902802700002602821700001802847700002102865700002002886700002802906700001902934700002102953700002202974700002502996700002203021700002103043700001703064700002403081700002303105700001703128700002203145700002303167700002003190700001903210700002103229700001603250700002603266700002003292700001903312700002103331700001903352700001903371700002003390700002803410700002103438700001903459700002003478700002003498700002703518700001403545700001303559700002103572700002503593700002403618700001703642700002403659700001803683700002203701700001403723700001803737700002003755700003003775700002003805700002103825700002403846700001803870700002203888700002903910700002303939700001503962700002103977700002103998700001604019700002004035700003104055700002004086700003004106700001904136700002204155700002004177700002404197700002004221700002204241700002004263700001704283700001904300700002704319700002404346700003104370700002004401700002104421700002704442700002604469700001504495700001204510700001804522700002804540700002404568700001604592700002204608700002304630700002604653700002304679700002704702700002004729700001704749700002204766700001904788700002504807700002004832700002304852700002104875700002404896700001904920700002404939700002104963700002004984700002405004700001905028700002405047700001805071700001905089700001805108700002205126700001705148700002305165700002205188700002505210700002705235700002705262700001905289700001905308700002305327700002305350700002005373700001705393700001805410700002405428700002105452700002305473700002505496700002305521700002105544700002505565700002205590700002005612700002205632700002605654700002005680700002005700700002405720700002705744700002505771700002805796700001905824700001905843700002005862700002205882700002105904700002805925700002305953700002505976700002106001700002606022856003606048 2012 eng d a1546-171800aGenome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.0 aGenomewide metaanalysis identifies 56 bone mineral density loci c2012 Apr 15 a491-5010 v443 aBone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10(-4), Bonferroni corrected), of which six reached P < 5 × 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.
10aBone Density10aComputational Biology10aEuropean Continental Ancestry Group10aExtracellular Matrix Proteins10aFemale10aFemur Neck10aFractures, Bone10aGene Expression Profiling10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aGlycoproteins10aHumans10aIntercellular Signaling Peptides and Proteins10aLow Density Lipoprotein Receptor-Related Protein-510aLumbar Vertebrae10aMale10aMitochondrial Membrane Transport Proteins10aOsteoporosis10aPhosphoproteins10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aRisk Factors10aSpectrin1 aEstrada, Karol1 aStyrkarsdottir, Unnur1 aEvangelou, Evangelos1 aHsu, Yi-Hsiang1 aDuncan, Emma, L1 aNtzani, Evangelia, E1 aOei, Ling1 aAlbagha, Omar, M E1 aAmin, Najaf1 aKemp, John, P1 aKoller, Daniel, L1 aLi, Guo1 aLiu, Ching-Ti1 aMinster, Ryan, L1 aMoayyeri, Alireza1 aVandenput, Liesbeth1 aWillner, Dana1 aXiao, Su-Mei1 aYerges-Armstrong, Laura, M1 aZheng, Hou-Feng1 aAlonso, Nerea1 aEriksson, Joel1 aKammerer, Candace, M1 aKaptoge, Stephen, K1 aLeo, Paul, J1 aThorleifsson, Gudmar1 aWilson, Scott, G1 aWilson, James, F1 aAalto, Ville1 aAlen, Markku1 aAragaki, Aaron, K1 aAspelund, Thor1 aCenter, Jacqueline, R1 aDailiana, Zoe1 aDuggan, David, J1 aGarcia, Melissa1 aGarcía-Giralt, Natalia1 aGiroux, Sylvie1 aHallmans, Göran1 aHocking, Lynne, J1 aHusted, Lise, Bjerre1 aJameson, Karen, A1 aKhusainova, Rita1 aKim, Ghi, Su1 aKooperberg, Charles1 aKoromila, Theodora1 aKruk, Marcin1 aLaaksonen, Marika1 aLaCroix, Andrea, Z1 aLee, Seung, Hun1 aLeung, Ping, C1 aLewis, Joshua, R1 aMasi, Laura1 aMencej-Bedrac, Simona1 aNguyen, Tuan, V1 aNogues, Xavier1 aPatel, Millan, S1 aPrezelj, Janez1 aRose, Lynda, M1 aScollen, Serena1 aSiggeirsdottir, Kristin1 aSmith, Albert, V1 aSvensson, Olle1 aTrompet, Stella1 aTrummer, Olivia1 avan Schoor, Natasja, M1 aWoo, Jean1 aZhu, Kun1 aBalcells, Susana1 aBrandi, Maria, Luisa1 aBuckley, Brendan, M1 aCheng, Sulin1 aChristiansen, Claus1 aCooper, Cyrus1 aDedoussis, George1 aFord, Ian1 aFrost, Morten1 aGoltzman, David1 aGonzález-Macías, Jesús1 aKähönen, Mika1 aKarlsson, Magnus1 aKhusnutdinova, Elza1 aKoh, Jung-Min1 aKollia, Panagoula1 aLangdahl, Bente, Lomholt1 aLeslie, William, D1 aLips, Paul1 aLjunggren, Osten1 aLorenc, Roman, S1 aMarc, Janja1 aMellström, Dan1 aObermayer-Pietsch, Barbara1 aOlmos, José, M1 aPettersson-Kymmer, Ulrika1 aReid, David, M1 aRiancho, José, A1 aRidker, Paul, M1 aRousseau, François1 aSlagboom, Eline1 aTang, Nelson, L S1 aUrreizti, Roser1 aVan Hul, Wim1 aViikari, Jorma1 aZarrabeitia, María, T1 aAulchenko, Yurii, S1 aCastano-Betancourt, Martha1 aGrundberg, Elin1 aHerrera, Lizbeth1 aIngvarsson, Thorvaldur1 aJohannsdottir, Hrefna1 aKwan, Tony1 aLi, Rui1 aLuben, Robert1 aMedina-Gómez, Carolina1 aPalsson, Stefan, Th1 aReppe, Sjur1 aRotter, Jerome, I1 aSigurdsson, Gunnar1 avan Meurs, Joyce, B J1 aVerlaan, Dominique1 aWilliams, Frances, M K1 aWood, Andrew, R1 aZhou, Yanhua1 aGautvik, Kaare, M1 aPastinen, Tomi1 aRaychaudhuri, Soumya1 aCauley, Jane, A1 aChasman, Daniel, I1 aClark, Graeme, R1 aCummings, Steven, R1 aDanoy, Patrick1 aDennison, Elaine, M1 aEastell, Richard1 aEisman, John, A1 aGudnason, Vilmundur1 aHofman, Albert1 aJackson, Rebecca, D1 aJones, Graeme1 aJukema, Wouter1 aKhaw, Kay-Tee1 aLehtimäki, Terho1 aLiu, Yongmei1 aLorentzon, Mattias1 aMcCloskey, Eugene1 aMitchell, Braxton, D1 aNandakumar, Kannabiran1 aNicholson, Geoffrey, C1 aOostra, Ben, A1 aPeacock, Munro1 aPols, Huibert, A P1 aPrince, Richard, L1 aRaitakari, Olli1 aReid, Ian, R1 aRobbins, John1 aSambrook, Philip, N1 aSham, Pak, Chung1 aShuldiner, Alan, R1 aTylavsky, Frances, A1 aDuijn, Cornelia, M1 aWareham, Nick, J1 aCupples, Adrienne, L1 aEcons, Michael, J1 aEvans, David, M1 aHarris, Tamara, B1 aKung, Annie, Wai Chee1 aPsaty, Bruce, M1 aReeve, Jonathan1 aSpector, Timothy, D1 aStreeten, Elizabeth, A1 aZillikens, Carola, M1 aThorsteinsdottir, Unnur1 aOhlsson, Claes1 aKarasik, David1 aRichards, Brent1 aBrown, Matthew, A1 aStefansson, Kari1 aUitterlinden, André, G1 aRalston, Stuart, H1 aIoannidis, John, P A1 aKiel, Douglas, P1 aRivadeneira, Fernando uhttps://chs-nhlbi.org/node/801603041nas a2200541 4500008004100000022001400041245007600055210006900131260000900200300001100209490000600220520147100226653002201697653002101719653002101740653004001761653003201801653001701833653001101850653003601861653001801897100002001915700002401935700002201959700002101981700002102002700002102023700002202044700002502066700002202091700002102113700001902134700002002153700002802173700002102201700001502222700002202237700002202259700002302281700002002304700002502324700002202349700002102371700002802392700002202420700002102442856003602463 2012 eng d a1932-620300aMulti-ethnic analysis of lipid-associated loci: the NHLBI CARe project.0 aMultiethnic analysis of lipidassociated loci the NHLBI CARe proj c2012 ae364730 v73 aBACKGROUND: Whereas it is well established that plasma lipid levels have substantial heritability within populations, it remains unclear how many of the genetic determinants reported in previous studies (largely performed in European American cohorts) are relevant in different ethnicities.
METHODOLOGY/PRINCIPAL FINDINGS: We tested a set of ∼50,000 polymorphisms from ∼2,000 candidate genes and genetic loci from genome-wide association studies (GWAS) for association with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) in 25,000 European Americans and 9,000 African Americans in the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe). We replicated associations for a number of genes in one or both ethnicities and identified a novel lipid-associated variant in a locus harboring ICAM1. We compared the architecture of genetic loci associated with lipids in both African Americans and European Americans and found that the same genes were relevant across ethnic groups but the specific associated variants at each gene often differed.
CONCLUSIONS/SIGNIFICANCE: We identify or provide further evidence for a number of genetic determinants of plasma lipid levels through population association studies. In many loci the determinants appear to differ substantially between African Americans and European Americans.
10aAfrican Americans10aCholesterol, HDL10aCholesterol, LDL10aEuropean Continental Ancestry Group10aGenetic Association Studies10aGenetic Loci10aHumans10aPolymorphism, Single Nucleotide10aTriglycerides1 aMusunuru, Kiran1 aRomaine, Simon, P R1 aLettre, Guillaume1 aWilson, James, G1 aVolcik, Kelly, A1 aTsai, Michael, Y1 aTaylor, Herman, A1 aSchreiner, Pamela, J1 aRotter, Jerome, I1 aRich, Stephen, S1 aRedline, Susan1 aPsaty, Bruce, M1 aPapanicolaou, George, J1 aOrdovas, Jose, M1 aLiu, Kiang1 aKrauss, Ronald, M1 aGlazer, Nicole, L1 aGabriel, Stacey, B1 aFornage, Myriam1 aCupples, Adrienne, L1 aBuxbaum, Sarah, G1 aBoerwinkle, Eric1 aBallantyne, Christie, M1 aKathiresan, Sekar1 aRader, Daniel, J uhttps://chs-nhlbi.org/node/138821848nas a2207177 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2012 eng d a1553-740400aNovel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.0 aNovel loci for adiponectin levels and their influence on type 2 c2012 ae10026070 v83 aCirculating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
10aAdiponectin10aAfrican Americans10aAsian Continental Ancestry Group10aCholesterol, HDL10aDiabetes Mellitus, Type 210aEuropean Continental Ancestry Group10aFemale10aGene Expression10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGlucose Tolerance Test10aHumans10aInsulin Resistance10aMale10aMetabolic Networks and Pathways10aPolymorphism, Single Nucleotide10aWaist-Hip Ratio1 aDastani, Zari1 aHivert, Marie-France1 aTimpson, Nicholas1 aPerry, John, R B1 aYuan, Xin1 aScott, Robert, A1 aHenneman, Peter1 aHeid, Iris, M1 aKizer, Jorge, R1 aLyytikäinen, Leo-Pekka1 aFuchsberger, Christian1 aTanaka, Toshiko1 aMorris, Andrew, P1 aSmall, Kerrin1 aIsaacs, Aaron1 aBeekman, Marian1 aCoassin, Stefan1 aLohman, Kurt1 aQi, Lu1 aKanoni, Stavroula1 aPankow, James, S1 aUh, Hae-Won1 aWu, Ying1 aBidulescu, Aurelian1 aRasmussen-Torvik, Laura, J1 aGreenwood, Celia, M T1 aLadouceur, Martin1 aGrimsby, Jonna1 aManning, Alisa, K1 aLiu, Ching-Ti1 aKooner, Jaspal1 aMooser, Vincent, E1 aVollenweider, Peter1 aKapur, Karen, A1 aChambers, John1 aWareham, Nicholas, J1 aLangenberg, Claudia1 aFrants, Rune1 aWillems-Vandijk, Ko1 aOostra, Ben, A1 aWillems, Sara, M1 aLamina, Claudia1 aWinkler, Thomas, W1 aPsaty, Bruce, M1 aTracy, Russell, P1 aBrody, Jennifer1 aChen, Ida1 aViikari, Jorma1 aKähönen, Mika1 aPramstaller, Peter, P1 aEvans, David, M1 aSt Pourcain, Beate1 aSattar, Naveed1 aWood, Andrew, R1 aBandinelli, Stefania1 aCarlson, Olga, D1 aEgan, Josephine, M1 aBöhringer, Stefan1 avan Heemst, Diana1 aKedenko, Lyudmyla1 aKristiansson, Kati1 aNuotio, Marja-Liisa1 aLoo, Britt-Marie1 aHarris, Tamara1 aGarcia, Melissa1 aKanaya, Alka1 aHaun, Margot1 aKlopp, Norman1 aWichmann, H-Erich1 aDeloukas, Panos1 aKatsareli, Efi1 aCouper, David, J1 aDuncan, Bruce, B1 aKloppenburg, Margreet1 aAdair, Linda, S1 aBorja, Judith, B1 aWilson, James, G1 aMusani, Solomon1 aGuo, Xiuqing1 aJohnson, Toby1 aSemple, Robert1 aTeslovich, Tanya, M1 aAllison, Matthew, A1 aRedline, Susan1 aBuxbaum, Sarah, G1 aMohlke, Karen, L1 aMeulenbelt, Ingrid1 aBallantyne, Christie, M1 aDedoussis, George, V1 aHu, Frank, B1 aLiu, Yongmei1 aPaulweber, Bernhard1 aSpector, Timothy, D1 aSlagboom, Eline1 aFerrucci, Luigi1 aJula, Antti1 aPerola, Markus1 aRaitakari, Olli1 aFlorez, Jose, C1 aSalomaa, Veikko1 aEriksson, Johan, G1 aFrayling, Timothy, M1 aHicks, Andrew, A1 aLehtimäki, Terho1 aSmith, George Davey1 aSiscovick, David, S1 aKronenberg, Florian1 aDuijn, Cornelia1 aLoos, Ruth, J F1 aWaterworth, Dawn, M1 aMeigs, James, B1 aDupuis, Josée1 aRichards, Brent1 aVoight, Benjamin, F1 aScott, Laura, J1 aSteinthorsdottir, Valgerdur1 aDina, Christian1 aWelch, Ryan, P1 aZeggini, Eleftheria1 aHuth, Cornelia1 aAulchenko, Yurii, S1 aThorleifsson, Gudmar1 aMcCulloch, Laura, J1 aFerreira, Teresa1 aGrallert, Harald1 aAmin, Najaf1 aWu, Guanming1 aWiller, Cristen, J1 aRaychaudhuri, Soumya1 aMcCarroll, Steve, A1 aHofmann, Oliver, M1 aSegrè, Ayellet, V1 aHoek, Mandy1 aNavarro, Pau1 aArdlie, Kristin1 aBalkau, Beverley1 aBenediktsson, Rafn1 aBennett, Amanda, J1 aBlagieva, Roza1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aBoström, Kristina, Bengtsson1 aBravenboer, Bert1 aBumpstead, Suzannah1 aBurtt, Noel, P1 aCharpentier, Guillaume1 aChines, Peter, S1 aCornelis, Marilyn1 aCrawford, Gabe1 aDoney, Alex, S F1 aElliott, Katherine, S1 aElliott, Amanda, L1 aErdos, Michael, R1 aFox, Caroline, S1 aFranklin, Christopher, S1 aGanser, Martha1 aGieger, Christian1 aGrarup, Niels1 aGreen, Todd1 aGriffin, Simon1 aGroves, Christopher, J1 aGuiducci, Candace1 aHadjadj, Samy1 aHassanali, Neelam1 aHerder, Christian1 aIsomaa, Bo1 aJackson, Anne, U1 aJohnson, Paul, R V1 aJørgensen, Torben1 aKao, Wen, H L1 aKong, Augustine1 aKraft, Peter1 aKuusisto, Johanna1 aLauritzen, Torsten1 aLi, Man1 aLieverse, Aloysius1 aLindgren, Cecilia, M1 aLyssenko, Valeriya1 aMarre, Michel1 aMeitinger, Thomas1 aMidthjell, Kristian1 aMorken, Mario, A1 aNarisu, Narisu1 aNilsson, Peter1 aOwen, Katharine, R1 aPayne, Felicity1 aPetersen, Ann-Kristin1 aPlatou, Carl1 aProença, Christine1 aProkopenko, Inga1 aRathmann, Wolfgang1 aRayner, William1 aRobertson, Neil, R1 aRocheleau, Ghislain1 aRoden, Michael1 aSampson, Michael, J1 aSaxena, Richa1 aShields, Beverley, M1 aShrader, Peter1 aSigurdsson, Gunnar1 aSparsø, Thomas1 aStrassburger, Klaus1 aStringham, Heather, M1 aSun, Qi1 aSwift, Amy, J1 aThorand, Barbara1 aTichet, Jean1 aTuomi, Tiinamaija1 avan Dam, Rob, M1 avan Haeften, Timon, W1 avan Herpt, Thijs1 avan Vliet-Ostaptchouk, Jana, V1 aWalters, Bragi, G1 aWeedon, Michael, N1 aWijmenga, Cisca1 aWitteman, Jacqueline1 aBergman, Richard, N1 aCauchi, Stephane1 aCollins, Francis, S1 aGloyn, Anna, L1 aGyllensten, Ulf1 aHansen, Torben1 aHide, Winston, A1 aHitman, Graham, A1 aHofman, Albert1 aHunter, David, J1 aHveem, Kristian1 aLaakso, Markku1 aMorris, Andrew, D1 aPalmer, Colin, N A1 aRudan, Igor1 aSijbrands, Eric1 aStein, Lincoln, D1 aTuomilehto, Jaakko1 aUitterlinden, Andre1 aWalker, Mark1 aWatanabe, Richard, M1 aAbecasis, Goncalo, R1 aBoehm, Bernhard, O1 aCampbell, Harry1 aDaly, Mark, J1 aHattersley, Andrew, T1 aPedersen, Oluf1 aBarroso, Inês1 aGroop, Leif1 aSladek, Rob1 aThorsteinsdottir, Unnur1 aWilson, James, F1 aIllig, Thomas1 aFroguel, Philippe1 aDuijn, Cornelia, M1 aStefansson, Kari1 aAltshuler, David1 aBoehnke, Michael1 aMcCarthy, Mark, I1 aSoranzo, Nicole1 aWheeler, Eleanor1 aGlazer, Nicole, L1 aBouatia-Naji, Nabila1 aMägi, Reedik1 aRandall, Joshua1 aElliott, Paul1 aRybin, Denis1 aDehghan, Abbas1 aHottenga, Jouke Jan1 aSong, Kijoung1 aGoel, Anuj1 aLajunen, Taina1 aDoney, Alex1 aCavalcanti-Proença, Christine1 aKumari, Meena1 aTimpson, Nicholas, J1 aZabena, Carina1 aIngelsson, Erik1 aAn, Ping1 aO'Connell, Jeffrey1 aLuan, Jian'an1 aElliott, Amanda1 aMcCarroll, Steven, A1 aRoccasecca, Rosa Maria1 aPattou, François1 aSethupathy, Praveen1 aAriyurek, Yavuz1 aBarter, Philip1 aBeilby, John, P1 aBen-Shlomo, Yoav1 aBergmann, Sven1 aBochud, Murielle1 aBonnefond, Amélie1 aBorch-Johnsen, Knut1 aBöttcher, Yvonne1 aBrunner, Eric1 aBumpstead, Suzannah, J1 aChen, Yii-Der Ida1 aChines, Peter1 aClarke, Robert1 aCoin, Lachlan, J M1 aCooper, Matthew, N1 aCrisponi, Laura1 aDay, Ian, N M1 aGeus, Eco, J C1 aDelplanque, Jerome1 aFedson, Annette, C1 aFischer-Rosinsky, Antje1 aForouhi, Nita, G1 aFranzosi, Maria Grazia1 aGalan, Pilar1 aGoodarzi, Mark, O1 aGraessler, Jürgen1 aGrundy, Scott1 aGwilliam, Rhian1 aHallmans, Göran1 aHammond, Naomi1 aHan, Xijing1 aHartikainen, Anna-Liisa1 aHayward, Caroline1 aHeath, Simon, C1 aHercberg, Serge1 aHillman, David, R1 aHingorani, Aroon, D1 aHui, Jennie1 aHung, Joe1 aKaakinen, Marika1 aKaprio, Jaakko1 aKesaniemi, Antero, Y1 aKivimaki, Mika1 aKnight, Beatrice1 aKoskinen, Seppo1 aKovacs, Peter1 aKyvik, Kirsten Ohm1 aLathrop, Mark, G1 aLawlor, Debbie, A1 aLe Bacquer, Olivier1 aLecoeur, Cécile1 aLi, Yun1 aMahley, Robert1 aMangino, Massimo1 aMartínez-Larrad, María Teresa1 aMcAteer, Jarred, B1 aMcPherson, Ruth1 aMeisinger, Christa1 aMelzer, David1 aMeyre, David1 aMitchell, Braxton, D1 aMukherjee, Sutapa1 aNaitza, Silvia1 aNeville, Matthew, J1 aOrrù, Marco1 aPakyz, Ruth1 aPaolisso, Giuseppe1 aPattaro, Cristian1 aPearson, Daniel1 aPeden, John, F1 aPedersen, Nancy, L1 aPfeiffer, Andreas, F H1 aPichler, Irene1 aPolasek, Ozren1 aPosthuma, Danielle1 aPotter, Simon, C1 aPouta, Anneli1 aProvince, Michael, A1 aRayner, Nigel, W1 aRice, Kenneth1 aRipatti, Samuli1 aRivadeneira, Fernando1 aRolandsson, Olov1 aSandbaek, Annelli1 aSandhu, Manjinder1 aSanna, Serena1 aSayer, Avan Aihie1 aScheet, Paul1 aSeedorf, Udo1 aSharp, Stephen, J1 aShields, Beverley1 aSigurðsson, Gunnar1 aSijbrands, Eric, J G1 aSilveira, Angela1 aSimpson, Laila1 aSingleton, Andrew1 aSmith, Nicholas, L1 aSovio, Ulla1 aSwift, Amy1 aSyddall, Holly1 aSyvänen, Ann-Christine1 aTönjes, Anke1 aUitterlinden, André, G1 aDijk, Ko Willems1 aVarma, Dhiraj1 aVisvikis-Siest, Sophie1 aVitart, Veronique1 aVogelzangs, Nicole1 aWaeber, Gérard1 aWagner, Peter, J1 aWalley, Andrew1 aWard, Kim, L1 aWatkins, Hugh1 aWild, Sarah, H1 aWillemsen, Gonneke1 aWitteman, Jaqueline, C M1 aYarnell, John, W G1 aZelenika, Diana1 aZethelius, Björn1 aZhai, Guangju1 aZhao, Jing Hua1 aZillikens, Carola, M1 aBorecki, Ingrid, B1 aMeneton, Pierre1 aMagnusson, Patrik, K E1 aNathan, David, M1 aWilliams, Gordon, H1 aSilander, Kaisa1 aBornstein, Stefan, R1 aSchwarz, Peter1 aSpranger, Joachim1 aKarpe, Fredrik1 aShuldiner, Alan, R1 aCooper, Cyrus1 aSerrano-Ríos, Manuel1 aLind, Lars1 aPalmer, Lyle, J1 aHu, Frank, B1 aFranks, Paul, W1 aEbrahim, Shah1 aMarmot, Michael1 aKao, Linda, W H1 aPramstaller, Peter Paul1 aWright, Alan, F1 aStumvoll, Michael1 aHamsten, Anders1 aBuchanan, Thomas, A1 aValle, Timo, T1 aRotter, Jerome, I1 aPenninx, Brenda, W J H1 aBoomsma, Dorret, I1 aCao, Antonio1 aScuteri, Angelo1 aSchlessinger, David1 aUda, Manuela1 aRuokonen, Aimo1 aJarvelin, Marjo-Riitta1 aPeltonen, Leena1 aMooser, Vincent1 aSladek, Robert1 aMusunuru, Kiran1 aSmith, Albert, V1 aEdmondson, Andrew, C1 aStylianou, Ioannis, M1 aKoseki, Masahiro1 aPirruccello, James, P1 aChasman, Daniel, I1 aJohansen, Christopher, T1 aFouchier, Sigrid, W1 aPeloso, Gina, M1 aBarbalic, Maja1 aRicketts, Sally, L1 aBis, Joshua, C1 aFeitosa, Mary, F1 aOrho-Melander, Marju1 aMelander, Olle1 aLi, Xiaohui1 aLi, Mingyao1 aCho, Yoon Shin1 aGo, Min Jin1 aKim, Young, Jin1 aLee, Jong-Young1 aPark, Taesung1 aKim, Kyunga1 aSim, Xueling1 aOng, Rick Twee-Hee1 aCroteau-Chonka, Damien, C1 aLange, Leslie, A1 aSmith, Joshua, D1 aZiegler, Andreas1 aZhang, Weihua1 aZee, Robert, Y L1 aWhitfield, John, B1 aThompson, John, R1 aSurakka, Ida1 aSpector, Tim, D1 aSmit, Johannes, H1 aSinisalo, Juha1 aScott, James1 aSaharinen, Juha1 aSabatti, Chiara1 aRose, Lynda, M1 aRoberts, Robert1 aRieder, Mark1 aParker, Alex, N1 aParé, Guillaume1 aO'Donnell, Christopher, J1 aNieminen, Markku, S1 aNickerson, Deborah, A1 aMontgomery, Grant, W1 aMcArdle, Wendy1 aMasson, David1 aMartin, Nicholas, G1 aMarroni, Fabio1 aLucas, Gavin1 aLuben, Robert1 aLokki, Marja-Liisa1 aLettre, Guillaume1 aLauner, Lenore, J1 aLakatta, Edward, G1 aLaaksonen, Reijo1 aKyvik, Kirsten, O1 aKönig, Inke, R1 aKhaw, Kay-Tee1 aKaplan, Lee, M1 aJohansson, Asa1 aJanssens, Cecile, J W1 aIgl, Wilmar1 aHovingh, Kees1 aHengstenberg, Christian1 aHavulinna, Aki, S1 aHastie, Nicholas, D1 aHarris, Tamara, B1 aHaritunians, Talin1 aHall, Alistair, S1 aGroop, Leif, C1 aGonzalez, Elena1 aFreimer, Nelson, B1 aErdmann, Jeanette1 aEjebe, Kenechi, G1 aDöring, Angela1 aDominiczak, Anna, F1 aDemissie, Serkalem1 aDeloukas, Panagiotis1 ade Faire, Ulf1 aCrawford, Gabriel1 aChen, Yii-der, I1 aCaulfield, Mark, J1 aBoekholdt, Matthijs1 aAssimes, Themistocles, L1 aQuertermous, Thomas1 aSeielstad, Mark1 aWong, Tien, Y1 aTai, E-Shyong1 aFeranil, Alan, B1 aKuzawa, Christopher, W1 aTaylor, Herman, A1 aGabriel, Stacey, B1 aHolm, Hilma1 aGudnason, Vilmundur1 aKrauss, Ronald, M1 aOrdovas, Jose, M1 aMunroe, Patricia, B1 aKooner, Jaspal, S1 aTall, Alan, R1 aHegele, Robert, A1 aKastelein, John, J P1 aSchadt, Eric, E1 aStrachan, David, P1 aReilly, Muredach, P1 aSamani, Nilesh, J1 aSchunkert, Heribert1 aCupples, Adrienne, L1 aSandhu, Manjinder, S1 aRidker, Paul, M1 aRader, Daniel, J1 aKathiresan, Sekar1 aDIAGRAM+ Consortium1 aMAGIC Consortium1 aGLGC Investigators1 aMuTHER Consortium1 aDIAGRAM Consortium1 aGIANT Consortium1 aGlobal B Pgen Consortium1 aProcardis Consortium1 aMAGIC investigators1 aGLGC Consortium uhttps://chs-nhlbi.org/node/137803691nas a2200649 4500008004100000022001400041245014200055210006900197260001300266300001100279490000800290520184900298653001202147653001202159653001602171653002002187653001002207653002302217653000902240653002502249653001102274653002002285653002202305653001802327653001302345653001102358653002502369653000902394653000902403653001302412653001402425653003602439653000902475653001702484653001602501100002802517700001802545700002202563700002102585700002302606700002402629700002202653700001802675700002302693700002002716700002302736700002102759700002202780700002102802700001902823700002802842700002502870700002402895700002402919710006202943856003603005 2012 eng d a1943-263100aUltraconserved elements in the human genome: association and transmission analyses of highly constrained single-nucleotide polymorphisms.0 aUltraconserved elements in the human genome association and tran c2012 Sep a253-660 v1923 aUltraconserved elements in the human genome likely harbor important biological functions as they are dosage sensitive and are able to direct tissue-specific expression. Because they are under purifying selection, variants in these elements may have a lower frequency in the population but a higher likelihood of association with complex traits. We tested a set of highly constrained SNPs (hcSNPs) distributed genome-wide among ultraconserved and nearly ultraconserved elements for association with seven traits related to reproductive (age at natural menopause, number of children, age at first child, and age at last child) and overall [longevity, body mass index (BMI), and height] fitness. Using up to 24,047 European-American samples from the National Heart, Lung, and Blood Institute Candidate Gene Association Resource (CARe), we observed an excess of associations with BMI and height. In an independent replication panel the most strongly associated SNPs showed an 8.4-fold enrichment of associations at the nominal level, including three variants in previously identified loci and one in a locus (DENND1A) previously shown to be associated with polycystic ovary syndrome. Finally, using 1430 family trios, we showed that the transmissions from heterozygous parents to offspring of the derived alleles of rare (frequency ≤ 0.5%) hcSNPs are not biased, particularly after adjusting for the rates of genotype missingness and error in the data. The lack of transmission bias ruled out an immediately and strongly deleterious effect due to the rare derived alleles, consistent with the observation that mice homozygous for the deletion of ultraconserved elements showed no overt phenotype. Our study also illustrated the importance of carefully modeling potential technical confounders when analyzing genotype data of rare variants.
10aAlleles10aAnimals10aBody Height10aBody Mass Index10aChild10aConserved Sequence10aDogs10aEvolution, Molecular10aFemale10aGenetic Fitness10aGenetic Variation10aGenome, Human10aGenotype10aHumans10aInheritance Patterns10aMale10aMice10aPedigree10aPhenotype10aPolymorphism, Single Nucleotide10aRats10aReproduction10aYoung Adult1 aChiang, Charleston, W K1 aLiu, Ching-Ti1 aLettre, Guillaume1 aLange, Leslie, A1 aJorgensen, Neal, W1 aKeating, Brendan, J1 aVedantam, Sailaja1 aNock, Nora, L1 aFranceschini, Nora1 aReiner, Alex, P1 aDemerath, Ellen, W1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aWilson, James, G1 aNorth, Kari, E1 aPapanicolaou, George, J1 aCupples, Adrienne, L1 aMurabito, Joanne, M1 aHirschhorn, Joel, N1 aGenetic Investigation of ANthropometric Traits Consortium uhttps://chs-nhlbi.org/node/154403560nas a2200709 4500008004100000022001400041245008800055210006900143260000900212300001100221490000600232520160600238653001001844653001201854653002101866653001901887653003401906653001001940653001101950653001901961653001301980653001301993653001002006653001102016653000902027653004402036653003602080653001602116653001602132653002702148100002002175700001302195700002402208700002302232700001902255700002002274700001702294700002302311700002502334700002002359700002402379700002202403700002202425700001902447700002202466700001702488700001702505700001902522700002002541700002002561700002102581700002602602700002402628700002102652700002402673700002302697700002102720700003002741700002202771700002102793856003602814 2013 eng d a1932-620300aBest practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium.0 aBest practices and joint calling of the HumanExome BeadChip the c2013 ae680950 v83 aGenotyping arrays are a cost effective approach when typing previously-identified genetic polymorphisms in large numbers of samples. One limitation of genotyping arrays with rare variants (e.g., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. Combining intensity data from large numbers of samples may increase the ability to accurately call the genotypes of rare variants. Approximately 62,000 ethnically diverse samples from eleven Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium cohorts were genotyped with the Illumina HumanExome BeadChip across seven genotyping centers. The raw data files for the samples were assembled into a single project for joint calling. To assess the quality of the joint calling, concordance of genotypes in a subset of individuals having both exome chip and exome sequence data was analyzed. After exclusion of low performing SNPs on the exome chip and non-overlap of SNPs derived from sequence data, genotypes of 185,119 variants (11,356 were monomorphic) were compared in 530 individuals that had whole exome sequence data. A total of 98,113,070 pairs of genotypes were tested and 99.77% were concordant, 0.14% had missing data, and 0.09% were discordant. We report that joint calling allows the ability to accurately genotype rare variation using array technology when large sample sizes are available and best practices are followed. The cluster file from this experiment is available at www.chargeconsortium.com/main/exomechip.
10aAging10aAlleles10aCluster Analysis10aCohort Studies10aContinental Population Groups10aExome10aFemale10aGene Frequency10aGenomics10aGenotype10aHeart10aHumans10aMale10aOligonucleotide Array Sequence Analysis10aPolymorphism, Single Nucleotide10aSample Size10aSelf Report10aSequence Analysis, DNA1 aGrove, Megan, L1 aYu, Bing1 aCochran, Barbara, J1 aHaritunians, Talin1 aBis, Joshua, C1 aTaylor, Kent, D1 aHansen, Mark1 aBorecki, Ingrid, B1 aCupples, Adrienne, L1 aFornage, Myriam1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aKathiresan, Sekar1 aKraaij, Robert1 aLauner, Lenore, J1 aLevy, Daniel1 aLiu, Yongmei1 aMosley, Thomas1 aPeloso, Gina, M1 aPsaty, Bruce, M1 aRich, Stephen, S1 aRivadeneira, Fernando1 aSiscovick, David, S1 aSmith, Albert, V1 aUitterlinden, Andre1 aDuijn, Cornelia, M1 aWilson, James, G1 aO'Donnell, Christopher, J1 aRotter, Jerome, I1 aBoerwinkle, Eric uhttps://chs-nhlbi.org/node/606710597nas a2203385 4500008004100000022001400041245009500055210006900150260001300219300001200232490000700244520112400251653002501375653002101400653002101421653002801442653001101470653003601481653001701517653001801534100001201552700002301564700002201587700002201609700001301631700002001644700002301664700002201687700001801709700001401727700002601741700001601767700002501783700003101808700002001839700001901859700002601878700002401904700002001928700001601948700002101964700002101985700002002006700002402026700002002050700002302070700002202093700002102115700002102136700001802157700002102175700001902196700001802215700002102233700002302254700002202277700001602299700001802315700002802333700002702361700002102388700002102409700002202430700003002452700001902482700002602501700002302527700001902550700002602569700001802595700001802613700002202631700001602653700002002669700001802689700001302707700002502720700001702745700002002762700002402782700002502806700002802831700002402859700002102883700002202904700001702926700001302943700001802956700001802974700001902992700001903011700002103030700002403051700002503075700002103100700002103121700002203142700002103164700002103185700002003206700001803226700002403244700003203268700001903300700002203319700002103341700002303362700002703385700002103412700002803433700002203461700002003483700002103503700001603524700001703540700001803557700002303575700002203598700002503620700001803645700001403663700001803677700002203695700001803717700002403735700002203759700001703781700002203798700002003820700002003840700002203860700002303882700002503905700002303930700002203953700001903975700002503994700002404019700002304043700001604066700001904082700002504101700002204126700001804148700002104166700002404187700002004211700002604231700001604257700001904273700001904292700002204311700001804333700002004351700002504371700002304396700001804419700002004437700002804457700002004485700002204505700002504527700002004552700001904572700002304591700001904614700002104633700002404654700001904678700002004697700002404717700002904741700002504770700002204795700002104817700002304838700002304861700002304884700002504907700001804932700002004950700002004970700002604990700002205016700002205038700002405060700002305084700001705107700002205124700001805146700002105164700002005185700002005205700002305225700002205248700001905270700002405289700002005313700002005333700002205353700002105375700002405396700001905420700001805439700002405457700002405481700002005505700002005525700002205545700002705567700001605594700002005610700001905630700002305649700001905672700002205691700002405713700002205737700001505759700002205774700002205796700001905818700001905837700001505856700002505871700002405896700002005920700002205940700002305962700002005985700002106005700002006026700002206046700002406068700002106092700002306113700001706136700002606153700002106179700002006200700002406220700002106244700002106265700002006286700002706306700002006333700002406353700002106377700002306398700002106421700002006442700002106462700002306483700002206506700001906528700002306547700002006570700002306590700002406613700002006637700002506657700002306682700003006705700002106735700002106756700002106777700002306798700002806821700002306849700002206872700002006894700002006914700002506934700002506959700002106984700002107005700002007026700002107046700002007067700002507087700001807112700002307130700002207153856003607175 2013 eng d a1546-171800aCommon variants associated with plasma triglycerides and risk for coronary artery disease.0 aCommon variants associated with plasma triglycerides and risk fo c2013 Nov a1345-520 v453 aTriglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
10aBiological Transport10aCholesterol, HDL10aCholesterol, LDL10aCoronary Artery Disease10aHumans10aPolymorphism, Single Nucleotide10aRisk Factors10aTriglycerides1 aDo, Ron1 aWiller, Cristen, J1 aSchmidt, Ellen, M1 aSengupta, Sebanti1 aGao, Chi1 aPeloso, Gina, M1 aGustafsson, Stefan1 aKanoni, Stavroula1 aGanna, Andrea1 aChen, Jin1 aBuchkovich, Martin, L1 aMora, Samia1 aBeckmann, Jacques, S1 aBragg-Gresham, Jennifer, L1 aChang, Hsing-Yi1 aDemirkan, Ayse1 aHertog, Heleen, M Den1 aDonnelly, Louise, A1 aEhret, Georg, B1 aEsko, Tõnu1 aFeitosa, Mary, F1 aFerreira, Teresa1 aFischer, Krista1 aFontanillas, Pierre1 aFraser, Ross, M1 aFreitag, Daniel, F1 aGurdasani, Deepti1 aHeikkilä, Kauko1 aHyppönen, Elina1 aIsaacs, Aaron1 aJackson, Anne, U1 aJohansson, Asa1 aJohnson, Toby1 aKaakinen, Marika1 aKettunen, Johannes1 aKleber, Marcus, E1 aLi, Xiaohui1 aLuan, Jian'an1 aLyytikäinen, Leo-Pekka1 aMagnusson, Patrik, K E1 aMangino, Massimo1 aMihailov, Evelin1 aMontasser, May, E1 aMüller-Nurasyid, Martina1 aNolte, Ilja, M1 aO'Connell, Jeffrey, R1 aPalmer, Cameron, D1 aPerola, Markus1 aPetersen, Ann-Kristin1 aSanna, Serena1 aSaxena, Richa1 aService, Susan, K1 aShah, Sonia1 aShungin, Dmitry1 aSidore, Carlo1 aSong, Ci1 aStrawbridge, Rona, J1 aSurakka, Ida1 aTanaka, Toshiko1 aTeslovich, Tanya, M1 aThorleifsson, Gudmar1 avan den Herik, Evita, G1 aVoight, Benjamin, F1 aVolcik, Kelly, A1 aWaite, Lindsay, L1 aWong, Andrew1 aWu, Ying1 aZhang, Weihua1 aAbsher, Devin1 aAsiki, Gershim1 aBarroso, Inês1 aBeen, Latonya, F1 aBolton, Jennifer, L1 aBonnycastle, Lori, L1 aBrambilla, Paolo1 aBurnett, Mary, S1 aCesana, Giancarlo1 aDimitriou, Maria1 aDoney, Alex, S F1 aDöring, Angela1 aElliott, Paul1 aEpstein, Stephen, E1 aEyjolfsson, Gudmundur, Ingi1 aGigante, Bruna1 aGoodarzi, Mark, O1 aGrallert, Harald1 aGravito, Martha, L1 aGroves, Christopher, J1 aHallmans, Göran1 aHartikainen, Anna-Liisa1 aHayward, Caroline1 aHernandez, Dena1 aHicks, Andrew, A1 aHolm, Hilma1 aHung, Yi-Jen1 aIllig, Thomas1 aJones, Michelle, R1 aKaleebu, Pontiano1 aKastelein, John, J P1 aKhaw, Kay-Tee1 aKim, Eric1 aKlopp, Norman1 aKomulainen, Pirjo1 aKumari, Meena1 aLangenberg, Claudia1 aLehtimäki, Terho1 aLin, Shih-Yi1 aLindström, Jaana1 aLoos, Ruth, J F1 aMach, François1 aMcArdle, Wendy, L1 aMeisinger, Christa1 aMitchell, Braxton, D1 aMüller, Gabrielle1 aNagaraja, Ramaiah1 aNarisu, Narisu1 aNieminen, Tuomo, V M1 aNsubuga, Rebecca, N1 aOlafsson, Isleifur1 aOng, Ken, K1 aPalotie, Aarno1 aPapamarkou, Theodore1 aPomilla, Cristina1 aPouta, Anneli1 aRader, Daniel, J1 aReilly, Muredach, P1 aRidker, Paul, M1 aRivadeneira, Fernando1 aRudan, Igor1 aRuokonen, Aimo1 aSamani, Nilesh1 aScharnagl, Hubert1 aSeeley, Janet1 aSilander, Kaisa1 aStančáková, Alena1 aStirrups, Kathleen1 aSwift, Amy, J1 aTiret, Laurence1 aUitterlinden, André, G1 avan Pelt, Joost1 aVedantam, Sailaja1 aWainwright, Nicholas1 aWijmenga, Cisca1 aWild, Sarah, H1 aWillemsen, Gonneke1 aWilsgaard, Tom1 aWilson, James, F1 aYoung, Elizabeth, H1 aZhao, Jing Hua1 aAdair, Linda, S1 aArveiler, Dominique1 aAssimes, Themistocles, L1 aBandinelli, Stefania1 aBennett, Franklyn1 aBochud, Murielle1 aBoehm, Bernhard, O1 aBoomsma, Dorret, I1 aBorecki, Ingrid, B1 aBornstein, Stefan, R1 aBovet, Pascal1 aBurnier, Michel1 aCampbell, Harry1 aChakravarti, Aravinda1 aChambers, John, C1 aChen, Yii-Der Ida1 aCollins, Francis, S1 aCooper, Richard, S1 aDanesh, John1 aDedoussis, George1 ade Faire, Ulf1 aFeranil, Alan, B1 aFerrieres, Jean1 aFerrucci, Luigi1 aFreimer, Nelson, B1 aGieger, Christian1 aGroop, Leif, C1 aGudnason, Vilmundur1 aGyllensten, Ulf1 aHamsten, Anders1 aHarris, Tamara, B1 aHingorani, Aroon1 aHirschhorn, Joel, N1 aHofman, Albert1 aHovingh, Kees1 aHsiung, Chao, Agnes1 aHumphries, Steve, E1 aHunt, Steven, C1 aHveem, Kristian1 aIribarren, Carlos1 aJarvelin, Marjo-Riitta1 aJula, Antti1 aKähönen, Mika1 aKaprio, Jaakko1 aKesäniemi, Antero1 aKivimaki, Mika1 aKooner, Jaspal, S1 aKoudstaal, Peter, J1 aKrauss, Ronald, M1 aKuh, Diana1 aKuusisto, Johanna1 aKyvik, Kirsten, O1 aLaakso, Markku1 aLakka, Timo, A1 aLind, Lars1 aLindgren, Cecilia, M1 aMartin, Nicholas, G1 aMärz, Winfried1 aMcCarthy, Mark, I1 aMcKenzie, Colin, A1 aMeneton, Pierre1 aMetspalu, Andres1 aMoilanen, Leena1 aMorris, Andrew, D1 aMunroe, Patricia, B1 aNjølstad, Inger1 aPedersen, Nancy, L1 aPower, Chris1 aPramstaller, Peter, P1 aPrice, Jackie, F1 aPsaty, Bruce, M1 aQuertermous, Thomas1 aRauramaa, Rainer1 aSaleheen, Danish1 aSalomaa, Veikko1 aSanghera, Dharambir, K1 aSaramies, Jouko1 aSchwarz, Peter, E H1 aSheu, Wayne, H-H1 aShuldiner, Alan, R1 aSiegbahn, Agneta1 aSpector, Tim, D1 aStefansson, Kari1 aStrachan, David, P1 aTayo, Bamidele, O1 aTremoli, Elena1 aTuomilehto, Jaakko1 aUusitupa, Matti1 aDuijn, Cornelia, M1 aVollenweider, Peter1 aWallentin, Lars1 aWareham, Nicholas, J1 aWhitfield, John, B1 aWolffenbuttel, Bruce, H R1 aAltshuler, David1 aOrdovas, Jose, M1 aBoerwinkle, Eric1 aPalmer, Colin, N A1 aThorsteinsdottir, Unnur1 aChasman, Daniel, I1 aRotter, Jerome, I1 aFranks, Paul, W1 aRipatti, Samuli1 aCupples, Adrienne, L1 aSandhu, Manjinder, S1 aRich, Stephen, S1 aBoehnke, Michael1 aDeloukas, Panos1 aMohlke, Karen, L1 aIngelsson, Erik1 aAbecasis, Goncalo, R1 aDaly, Mark, J1 aNeale, Benjamin, M1 aKathiresan, Sekar uhttps://chs-nhlbi.org/node/801410661nas a2203397 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2013 eng d a1546-171800aDiscovery and refinement of loci associated with lipid levels.0 aDiscovery and refinement of loci associated with lipid levels c2013 Nov a1274-12830 v453 aLevels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.
10aAfrican Continental Ancestry Group10aAsian Continental Ancestry Group10aCholesterol, HDL10aCholesterol, LDL10aCoronary Artery Disease10aEuropean Continental Ancestry Group10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aHumans10aLipids10aTriglycerides1 aWiller, Cristen, J1 aSchmidt, Ellen, M1 aSengupta, Sebanti1 aPeloso, Gina, M1 aGustafsson, Stefan1 aKanoni, Stavroula1 aGanna, Andrea1 aChen, Jin1 aBuchkovich, Martin, L1 aMora, Samia1 aBeckmann, Jacques, S1 aBragg-Gresham, Jennifer, L1 aChang, Hsing-Yi1 aDemirkan, Ayse1 aHertog, Heleen, M Den1 aDo, Ron1 aDonnelly, Louise, A1 aEhret, Georg, B1 aEsko, Tõnu1 aFeitosa, Mary, F1 aFerreira, Teresa1 aFischer, Krista1 aFontanillas, Pierre1 aFraser, Ross, M1 aFreitag, Daniel, F1 aGurdasani, Deepti1 aHeikkilä, Kauko1 aHyppönen, Elina1 aIsaacs, Aaron1 aJackson, Anne, U1 aJohansson, Asa1 aJohnson, Toby1 aKaakinen, Marika1 aKettunen, Johannes1 aKleber, Marcus, E1 aLi, Xiaohui1 aLuan, Jian'an1 aLyytikäinen, Leo-Pekka1 aMagnusson, Patrik, K E1 aMangino, Massimo1 aMihailov, Evelin1 aMontasser, May, E1 aMüller-Nurasyid, Martina1 aNolte, Ilja, M1 aO'Connell, Jeffrey, R1 aPalmer, Cameron, D1 aPerola, Markus1 aPetersen, Ann-Kristin1 aSanna, Serena1 aSaxena, Richa1 aService, Susan, K1 aShah, Sonia1 aShungin, Dmitry1 aSidore, Carlo1 aSong, Ci1 aStrawbridge, Rona, J1 aSurakka, Ida1 aTanaka, Toshiko1 aTeslovich, Tanya, M1 aThorleifsson, Gudmar1 avan den Herik, Evita, G1 aVoight, Benjamin, F1 aVolcik, Kelly, A1 aWaite, Lindsay, L1 aWong, Andrew1 aWu, Ying1 aZhang, Weihua1 aAbsher, Devin1 aAsiki, Gershim1 aBarroso, Inês1 aBeen, Latonya, F1 aBolton, Jennifer, L1 aBonnycastle, Lori, L1 aBrambilla, Paolo1 aBurnett, Mary, S1 aCesana, Giancarlo1 aDimitriou, Maria1 aDoney, Alex, S F1 aDöring, Angela1 aElliott, Paul1 aEpstein, Stephen, E1 aEyjolfsson, Gudmundur, Ingi1 aGigante, Bruna1 aGoodarzi, Mark, O1 aGrallert, Harald1 aGravito, Martha, L1 aGroves, Christopher, J1 aHallmans, Göran1 aHartikainen, Anna-Liisa1 aHayward, Caroline1 aHernandez, Dena1 aHicks, Andrew, A1 aHolm, Hilma1 aHung, Yi-Jen1 aIllig, Thomas1 aJones, Michelle, R1 aKaleebu, Pontiano1 aKastelein, John, J P1 aKhaw, Kay-Tee1 aKim, Eric1 aKlopp, Norman1 aKomulainen, Pirjo1 aKumari, Meena1 aLangenberg, Claudia1 aLehtimäki, Terho1 aLin, Shih-Yi1 aLindström, Jaana1 aLoos, Ruth, J F1 aMach, François1 aMcArdle, Wendy, L1 aMeisinger, Christa1 aMitchell, Braxton, D1 aMüller, Gabrielle1 aNagaraja, Ramaiah1 aNarisu, Narisu1 aNieminen, Tuomo, V M1 aNsubuga, Rebecca, N1 aOlafsson, Isleifur1 aOng, Ken, K1 aPalotie, Aarno1 aPapamarkou, Theodore1 aPomilla, Cristina1 aPouta, Anneli1 aRader, Daniel, J1 aReilly, Muredach, P1 aRidker, Paul, M1 aRivadeneira, Fernando1 aRudan, Igor1 aRuokonen, Aimo1 aSamani, Nilesh1 aScharnagl, Hubert1 aSeeley, Janet1 aSilander, Kaisa1 aStančáková, Alena1 aStirrups, Kathleen1 aSwift, Amy, J1 aTiret, Laurence1 aUitterlinden, André, G1 avan Pelt, Joost1 aVedantam, Sailaja1 aWainwright, Nicholas1 aWijmenga, Cisca1 aWild, Sarah, H1 aWillemsen, Gonneke1 aWilsgaard, Tom1 aWilson, James, F1 aYoung, Elizabeth, H1 aZhao, Jing Hua1 aAdair, Linda, S1 aArveiler, Dominique1 aAssimes, Themistocles, L1 aBandinelli, Stefania1 aBennett, Franklyn1 aBochud, Murielle1 aBoehm, Bernhard, O1 aBoomsma, Dorret, I1 aBorecki, Ingrid, B1 aBornstein, Stefan, R1 aBovet, Pascal1 aBurnier, Michel1 aCampbell, Harry1 aChakravarti, Aravinda1 aChambers, John, C1 aChen, Yii-Der Ida1 aCollins, Francis, S1 aCooper, Richard, S1 aDanesh, John1 aDedoussis, George1 ade Faire, Ulf1 aFeranil, Alan, B1 aFerrieres, Jean1 aFerrucci, Luigi1 aFreimer, Nelson, B1 aGieger, Christian1 aGroop, Leif, C1 aGudnason, Vilmundur1 aGyllensten, Ulf1 aHamsten, Anders1 aHarris, Tamara, B1 aHingorani, Aroon1 aHirschhorn, Joel, N1 aHofman, Albert1 aHovingh, Kees1 aHsiung, Chao, Agnes1 aHumphries, Steve, E1 aHunt, Steven, C1 aHveem, Kristian1 aIribarren, Carlos1 aJarvelin, Marjo-Riitta1 aJula, Antti1 aKähönen, Mika1 aKaprio, Jaakko1 aKesäniemi, Antero1 aKivimaki, Mika1 aKooner, Jaspal, S1 aKoudstaal, Peter, J1 aKrauss, Ronald, M1 aKuh, Diana1 aKuusisto, Johanna1 aKyvik, Kirsten, O1 aLaakso, Markku1 aLakka, Timo, A1 aLind, Lars1 aLindgren, Cecilia, M1 aMartin, Nicholas, G1 aMärz, Winfried1 aMcCarthy, Mark, I1 aMcKenzie, Colin, A1 aMeneton, Pierre1 aMetspalu, Andres1 aMoilanen, Leena1 aMorris, Andrew, D1 aMunroe, Patricia, B1 aNjølstad, Inger1 aPedersen, Nancy, L1 aPower, Chris1 aPramstaller, Peter, P1 aPrice, Jackie, F1 aPsaty, Bruce, M1 aQuertermous, Thomas1 aRauramaa, Rainer1 aSaleheen, Danish1 aSalomaa, Veikko1 aSanghera, Dharambir, K1 aSaramies, Jouko1 aSchwarz, Peter, E H1 aSheu, Wayne, H-H1 aShuldiner, Alan, R1 aSiegbahn, Agneta1 aSpector, Tim, D1 aStefansson, Kari1 aStrachan, David, P1 aTayo, Bamidele, O1 aTremoli, Elena1 aTuomilehto, Jaakko1 aUusitupa, Matti1 aDuijn, Cornelia, M1 aVollenweider, Peter1 aWallentin, Lars1 aWareham, Nicholas, J1 aWhitfield, John, B1 aWolffenbuttel, Bruce, H R1 aOrdovas, Jose, M1 aBoerwinkle, Eric1 aPalmer, Colin, N A1 aThorsteinsdottir, Unnur1 aChasman, Daniel, I1 aRotter, Jerome, I1 aFranks, Paul, W1 aRipatti, Samuli1 aCupples, Adrienne, L1 aSandhu, Manjinder, S1 aRich, Stephen, S1 aBoehnke, Michael1 aDeloukas, Panos1 aKathiresan, Sekar1 aMohlke, Karen, L1 aIngelsson, Erik1 aAbecasis, Goncalo, R1 aGlobal Lipids Genetics Consortium uhttps://chs-nhlbi.org/node/615406047nas a2201393 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2013 eng d a1553-740400aGenome-wide association of body fat distribution in African ancestry populations suggests new loci.0 aGenomewide association of body fat distribution in African ances c2013 ae10036810 v93 aCentral obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0 × 10(-6) were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8); RREB1: p = 5.7 × 10(-8)). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.
10aAdiposity10aAfrican Continental Ancestry Group10aBody Fat Distribution10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenome-Wide Association Study10aHumans10aMale10aObesity10aPolymorphism, Single Nucleotide10aWaist-Hip Ratio1 aLiu, Ching-Ti1 aMonda, Keri, L1 aTaylor, Kira, C1 aLange, Leslie1 aDemerath, Ellen, W1 aPalmas, Walter1 aWojczynski, Mary, K1 aEllis, Jaclyn, C1 aVitolins, Mara, Z1 aLiu, Simin1 aPapanicolaou, George, J1 aIrvin, Marguerite, R1 aXue, Luting1 aGriffin, Paula, J1 aNalls, Michael, A1 aAdeyemo, Adebowale1 aLiu, Jiankang1 aLi, Guo1 aRuiz-Narvaez, Edward, A1 aChen, Wei-Min1 aChen, Fang1 aHenderson, Brian, E1 aMillikan, Robert, C1 aAmbrosone, Christine, B1 aStrom, Sara, S1 aGuo, Xiuqing1 aAndrews, Jeanette, S1 aSun, Yan, V1 aMosley, Thomas, H1 aYanek, Lisa, R1 aShriner, Daniel1 aHaritunians, Talin1 aRotter, Jerome, I1 aSpeliotes, Elizabeth, K1 aSmith, Megan1 aRosenberg, Lynn1 aMychaleckyj, Josyf1 aNayak, Uma1 aSpruill, Ida1 aGarvey, Timothy1 aPettaway, Curtis1 aNyante, Sarah1 aBandera, Elisa, V1 aBritton, Angela, F1 aZonderman, Alan, B1 aRasmussen-Torvik, Laura, J1 aChen, Yii-Der Ida1 aDing, Jingzhong1 aLohman, Kurt1 aKritchevsky, Stephen, B1 aZhao, Wei1 aPeyser, Patricia, A1 aKardia, Sharon, L R1 aKabagambe, Edmond1 aBroeckel, Ulrich1 aChen, Guanjie1 aZhou, Jie1 aWassertheil-Smoller, Sylvia1 aNeuhouser, Marian, L1 aRampersaud, Evadnie1 aPsaty, Bruce1 aKooperberg, Charles1 aManson, JoAnn, E1 aKuller, Lewis, H1 aOchs-Balcom, Heather, M1 aJohnson, Karen, C1 aSucheston, Lara1 aOrdovas, Jose, M1 aPalmer, Julie, R1 aHaiman, Christopher, A1 aMcKnight, Barbara1 aHoward, Barbara, V1 aBecker, Diane, M1 aBielak, Lawrence, F1 aLiu, Yongmei1 aAllison, Matthew, A1 aGrant, Struan, F A1 aBurke, Gregory, L1 aPatel, Sanjay, R1 aSchreiner, Pamela, J1 aBorecki, Ingrid, B1 aEvans, Michele, K1 aTaylor, Herman1 aSale, Michèle, M1 aHoward, Virginia1 aCarlson, Christopher, S1 aRotimi, Charles, N1 aCushman, Mary1 aHarris, Tamara, B1 aReiner, Alexander, P1 aCupples, Adrienne, L1 aNorth, Kari, E1 aFox, Caroline, S uhttps://chs-nhlbi.org/node/628712626nas a2204177 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2013 eng d a1546-171800aGenome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.0 aGenomewide metaanalysis identifies 11 new loci for anthropometri c2013 May a501-120 v453 aApproaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
10aAnthropometry10aBody Height10aBody Mass Index10aCase-Control Studies10aEuropean Continental Ancestry Group10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aHumans10aMeta-Analysis as Topic10aObesity10aPhenotype10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci10aWaist-Hip Ratio1 aBerndt, Sonja, I1 aGustafsson, Stefan1 aMägi, Reedik1 aGanna, Andrea1 aWheeler, Eleanor1 aFeitosa, Mary, F1 aJustice, Anne, E1 aMonda, Keri, L1 aCroteau-Chonka, Damien, C1 aDay, Felix, R1 aEsko, Tõnu1 aFall, Tove1 aFerreira, Teresa1 aGentilini, Davide1 aJackson, Anne, U1 aLuan, Jian'an1 aRandall, Joshua, C1 aVedantam, Sailaja1 aWiller, Cristen, J1 aWinkler, Thomas, W1 aWood, Andrew, R1 aWorkalemahu, Tsegaselassie1 aHu, Yi-Juan1 aLee, Sang, Hong1 aLiang, Liming1 aLin, Dan-Yu1 aMin, Josine, L1 aNeale, Benjamin, M1 aThorleifsson, Gudmar1 aYang, Jian1 aAlbrecht, Eva1 aAmin, Najaf1 aBragg-Gresham, Jennifer, L1 aCadby, Gemma1 aHeijer, Martin, den1 aEklund, Niina1 aFischer, Krista1 aGoel, Anuj1 aHottenga, Jouke-Jan1 aHuffman, Jennifer, E1 aJarick, Ivonne1 aJohansson, Asa1 aJohnson, Toby1 aKanoni, Stavroula1 aKleber, Marcus, E1 aKönig, Inke, R1 aKristiansson, Kati1 aKutalik, Zoltán1 aLamina, Claudia1 aLecoeur, Cécile1 aLi, Guo1 aMangino, Massimo1 aMcArdle, Wendy, L1 aMedina-Gómez, Carolina1 aMüller-Nurasyid, Martina1 aNgwa, Julius, S1 aNolte, Ilja, M1 aPaternoster, Lavinia1 aPechlivanis, Sonali1 aPerola, Markus1 aPeters, Marjolein, J1 aPreuss, Michael1 aRose, Lynda, M1 aShi, Jianxin1 aShungin, Dmitry1 aSmith, Albert, Vernon1 aStrawbridge, Rona, J1 aSurakka, Ida1 aTeumer, Alexander1 aTrip, Mieke, D1 aTyrer, Jonathan1 avan Vliet-Ostaptchouk, Jana, V1 aVandenput, Liesbeth1 aWaite, Lindsay, L1 aZhao, Jing Hua1 aAbsher, Devin1 aAsselbergs, Folkert, W1 aAtalay, Mustafa1 aAttwood, Antony, P1 aBalmforth, Anthony, J1 aBasart, Hanneke1 aBeilby, John1 aBonnycastle, Lori, L1 aBrambilla, Paolo1 aBruinenberg, Marcel1 aCampbell, Harry1 aChasman, Daniel, I1 aChines, Peter, S1 aCollins, Francis, S1 aConnell, John, M1 aCookson, William, O1 ade Faire, Ulf1 ade Vegt, Femmie1 aDei, Mariano1 aDimitriou, Maria1 aEdkins, Sarah1 aEstrada, Karol1 aEvans, David, M1 aFarrall, Martin1 aFerrario, Marco, M1 aFerrieres, Jean1 aFranke, Lude1 aFrau, Francesca1 aGejman, Pablo, V1 aGrallert, Harald1 aGrönberg, Henrik1 aGudnason, Vilmundur1 aHall, Alistair, S1 aHall, Per1 aHartikainen, Anna-Liisa1 aHayward, Caroline1 aHeard-Costa, Nancy, L1 aHeath, Andrew, C1 aHebebrand, Johannes1 aHomuth, Georg1 aHu, Frank, B1 aHunt, Sarah, E1 aHyppönen, Elina1 aIribarren, Carlos1 aJacobs, Kevin, B1 aJansson, John-Olov1 aJula, Antti1 aKähönen, Mika1 aKathiresan, Sekar1 aKee, Frank1 aKhaw, Kay-Tee1 aKivimaki, Mika1 aKoenig, Wolfgang1 aKraja, Aldi, T1 aKumari, Meena1 aKuulasmaa, Kari1 aKuusisto, Johanna1 aLaitinen, Jaana, H1 aLakka, Timo, A1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLind, Lars1 aLindström, Jaana1 aLiu, Jianjun1 aLiuzzi, Antonio1 aLokki, Marja-Liisa1 aLorentzon, Mattias1 aMadden, Pamela, A1 aMagnusson, Patrik, K1 aManunta, Paolo1 aMarek, Diana1 aMärz, Winfried1 aLeach, Irene, Mateo1 aMcKnight, Barbara1 aMedland, Sarah, E1 aMihailov, Evelin1 aMilani, Lili1 aMontgomery, Grant, W1 aMooser, Vincent1 aMühleisen, Thomas, W1 aMunroe, Patricia, B1 aMusk, Arthur, W1 aNarisu, Narisu1 aNavis, Gerjan1 aNicholson, George1 aNohr, Ellen, A1 aOng, Ken, K1 aOostra, Ben, A1 aPalmer, Colin, N A1 aPalotie, Aarno1 aPeden, John, F1 aPedersen, Nancy1 aPeters, Annette1 aPolasek, Ozren1 aPouta, Anneli1 aPramstaller, Peter, P1 aProkopenko, Inga1 aPütter, Carolin1 aRadhakrishnan, Aparna1 aRaitakari, Olli1 aRendon, Augusto1 aRivadeneira, Fernando1 aRudan, Igor1 aSaaristo, Timo, E1 aSambrook, Jennifer, G1 aSanders, Alan, R1 aSanna, Serena1 aSaramies, Jouko1 aSchipf, Sabine1 aSchreiber, Stefan1 aSchunkert, Heribert1 aShin, So-Youn1 aSignorini, Stefano1 aSinisalo, Juha1 aSkrobek, Boris1 aSoranzo, Nicole1 aStančáková, Alena1 aStark, Klaus1 aStephens, Jonathan, C1 aStirrups, Kathleen1 aStolk, Ronald, P1 aStumvoll, Michael1 aSwift, Amy, J1 aTheodoraki, Eirini, V1 aThorand, Barbara1 aTrégouët, David-Alexandre1 aTremoli, Elena1 avan der Klauw, Melanie, M1 avan Meurs, Joyce, B J1 aVermeulen, Sita, H1 aViikari, Jorma1 aVirtamo, Jarmo1 aVitart, Veronique1 aWaeber, Gérard1 aWang, Zhaoming1 aWiden, Elisabeth1 aWild, Sarah, H1 aWillemsen, Gonneke1 aWinkelmann, Bernhard, R1 aWitteman, Jacqueline, C M1 aWolffenbuttel, Bruce, H R1 aWong, Andrew1 aWright, Alan, F1 aZillikens, Carola, M1 aAmouyel, Philippe1 aBoehm, Bernhard, O1 aBoerwinkle, Eric1 aBoomsma, Dorret, I1 aCaulfield, Mark, J1 aChanock, Stephen, J1 aCupples, Adrienne, L1 aCusi, Daniele1 aDedoussis, George, V1 aErdmann, Jeanette1 aEriksson, Johan, G1 aFranks, Paul, W1 aFroguel, Philippe1 aGieger, Christian1 aGyllensten, Ulf1 aHamsten, Anders1 aHarris, Tamara, B1 aHengstenberg, Christian1 aHicks, Andrew, A1 aHingorani, Aroon1 aHinney, Anke1 aHofman, Albert1 aHovingh, Kees, G1 aHveem, Kristian1 aIllig, Thomas1 aJarvelin, Marjo-Riitta1 aJöckel, Karl-Heinz1 aKeinanen-Kiukaanniemi, Sirkka, M1 aKiemeney, Lambertus, A1 aKuh, Diana1 aLaakso, Markku1 aLehtimäki, Terho1 aLevinson, Douglas, F1 aMartin, Nicholas, G1 aMetspalu, Andres1 aMorris, Andrew, D1 aNieminen, Markku, S1 aNjølstad, Inger1 aOhlsson, Claes1 aOldehinkel, Albertine, J1 aOuwehand, Willem, H1 aPalmer, Lyle, J1 aPenninx, Brenda1 aPower, Chris1 aProvince, Michael, A1 aPsaty, Bruce, M1 aQi, Lu1 aRauramaa, Rainer1 aRidker, Paul, M1 aRipatti, Samuli1 aSalomaa, Veikko1 aSamani, Nilesh, J1 aSnieder, Harold1 aSørensen, Thorkild, I A1 aSpector, Timothy, D1 aStefansson, Kari1 aTönjes, Anke1 aTuomilehto, Jaakko1 aUitterlinden, André, G1 aUusitupa, Matti1 aHarst, Pim1 aVollenweider, Peter1 aWallaschofski, Henri1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWichmann, H-Erich1 aWilson, James, F1 aAbecasis, Goncalo, R1 aAssimes, Themistocles, L1 aBarroso, Inês1 aBoehnke, Michael1 aBorecki, Ingrid, B1 aDeloukas, Panos1 aFox, Caroline, S1 aFrayling, Timothy1 aGroop, Leif, C1 aHaritunian, Talin1 aHeid, Iris, M1 aHunter, David1 aKaplan, Robert, C1 aKarpe, Fredrik1 aMoffatt, Miriam, F1 aMohlke, Karen, L1 aO'Connell, Jeffrey, R1 aPawitan, Yudi1 aSchadt, Eric, E1 aSchlessinger, David1 aSteinthorsdottir, Valgerdur1 aStrachan, David, P1 aThorsteinsdottir, Unnur1 aDuijn, Cornelia, M1 aVisscher, Peter, M1 aDi Blasio, Anna, Maria1 aHirschhorn, Joel, N1 aLindgren, Cecilia, M1 aMorris, Andrew, P1 aMeyre, David1 aScherag, Andre1 aMcCarthy, Mark, I1 aSpeliotes, Elizabeth, K1 aNorth, Kari, E1 aLoos, Ruth, J F1 aIngelsson, Erik uhttps://chs-nhlbi.org/node/615205845nas a2201189 4500008004100000022001400041245012300055210006900178260001300247300001300260490000700273520235900280653001202639653002002651653002002671653002602691653001702717653002102734653001802755653004002773653003002813653002202843653003302865653003802898653003402936653001302970653001102983653001502994653001203009653003603021653002403057653002803081653003103109100002003140700002003160700002603180700002503206700002403231700002803255700002303283700002203306700002403328700001803352700001903370700002003389700002103409700001903430700001903449700001103468700002303479700002903502700002503531700002103556700002403577700001803601700002003619700002103639700002303660700002503683700002203708700002303730700001903753700001403772700002503786700001903811700002003830700002103850700001903871700001703890700002803907700001903935700002103954700002103975700002003996700002404016700002104040700002804061700001704089700003104106700002004137700002104157700002004178700002004198700002504218700002204243700002404265700002104289700002304310700002004333700002804353700002204381700002004403700002504423700002204448700002504470700003004495700002004525700002204545700002504567700002704592856003604619 2013 eng d a1938-320700aGenome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.0 aGenomewide metaanalysis of observational studies shows common ge c2013 Jun a1395-4020 v973 aBACKGROUND: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.
OBJECTIVE: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.
DESIGN: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.
RESULTS: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(-7)).
CONCLUSION: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
10aAlleles10aAtherosclerosis10aBody Mass Index10aDietary Carbohydrates10aDietary Fats10aDietary Proteins10aEnergy Intake10aEuropean Continental Ancestry Group10aFibroblast Growth Factors10aFollow-Up Studies10aGene-Environment Interaction10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aHumans10aLife Style10aObesity10aPolymorphism, Single Nucleotide10aProspective Studies10aQuantitative Trait Loci10aSurveys and Questionnaires1 aTanaka, Toshiko1 aNgwa, Julius, S1 avan Rooij, Frank, J A1 aZillikens, Carola, M1 aWojczynski, Mary, K1 aFrazier-Wood, Alexis, C1 aHouston, Denise, K1 aKanoni, Stavroula1 aLemaitre, Rozenn, N1 aLuan, Jian'an1 aMikkilä, Vera1 aRenstrom, Frida1 aSonestedt, Emily1 aZhao, Jing Hua1 aChu, Audrey, Y1 aQi, Lu1 aChasman, Daniel, I1 aOtto, Marcia, C de Olive1 aDhurandhar, Emily, J1 aFeitosa, Mary, F1 aJohansson, Ingegerd1 aKhaw, Kay-Tee1 aLohman, Kurt, K1 aManichaikul, Ani1 aMcKeown, Nicola, M1 aMozaffarian, Dariush1 aSingleton, Andrew1 aStirrups, Kathleen1 aViikari, Jorma1 aYe, Zheng1 aBandinelli, Stefania1 aBarroso, Inês1 aDeloukas, Panos1 aForouhi, Nita, G1 aHofman, Albert1 aLiu, Yongmei1 aLyytikäinen, Leo-Pekka1 aNorth, Kari, E1 aDimitriou, Maria1 aHallmans, Göran1 aKähönen, Mika1 aLangenberg, Claudia1 aOrdovas, Jose, M1 aUitterlinden, André, G1 aHu, Frank, B1 aKalafati, Ioanna-Panagiota1 aRaitakari, Olli1 aFranco, Oscar, H1 aJohnson, Andrew1 aEmilsson, Valur1 aSchrack, Jennifer, A1 aSemba, Richard, D1 aSiscovick, David, S1 aArnett, Donna, K1 aBorecki, Ingrid, B1 aFranks, Paul, W1 aKritchevsky, Stephen, B1 aLehtimäki, Terho1 aLoos, Ruth, J F1 aOrho-Melander, Marju1 aRotter, Jerome, I1 aWareham, Nicholas, J1 aWitteman, Jacqueline, C M1 aFerrucci, Luigi1 aDedoussis, George1 aCupples, Adrienne, L1 aNettleton, Jennifer, A uhttps://chs-nhlbi.org/node/616304700nas a2200961 4500008004100000022001400041245019200055210006900247260001300316300001100329490000800340520188800348653001802236653001102254653001702265653001102282653001202293653001402305653000902319653003602328653001902364653002502383100001702408700002002425700002002445700002402465700001802489700002102507700002302528700002102551700002202572700002202594700002402616700002102640700001902661700001902680700002102699700002002720700002602740700002502766700001802791700001902809700002402828700002002852700002102872700002302893700001702916700002202933700002502955700002202980700001703002700002503019700002903044700002803073700002803101700001903129700002703148700001903175700001503194700002203209700001903231700002103250700002103271700002303292700002503315700002503340700002003365700001703385700002003402700002003422700002003442700002803462700002503490700002103515700002203536700002403558700003003582700002003612700002003632700002303652700002703675856003603702 2013 eng d a1541-610000aHigher magnesium intake is associated with lower fasting glucose and insulin, with no evidence of interaction with select genetic loci, in a meta-analysis of 15 CHARGE Consortium Studies.0 aHigher magnesium intake is associated with lower fasting glucose c2013 Mar a345-530 v1433 aFavorable associations between magnesium intake and glycemic traits, such as fasting glucose and insulin, are observed in observational and clinical studies, but whether genetic variation affects these associations is largely unknown. We hypothesized that single nucleotide polymorphisms (SNPs) associated with either glycemic traits or magnesium metabolism affect the association between magnesium intake and fasting glucose and insulin. Fifteen studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided data from up to 52,684 participants of European descent without known diabetes. In fixed-effects meta-analyses, we quantified 1) cross-sectional associations of dietary magnesium intake with fasting glucose (mmol/L) and insulin (ln-pmol/L) and 2) interactions between magnesium intake and SNPs related to fasting glucose (16 SNPs), insulin (2 SNPs), or magnesium (8 SNPs) on fasting glucose and insulin. After adjustment for age, sex, energy intake, BMI, and behavioral risk factors, magnesium (per 50-mg/d increment) was inversely associated with fasting glucose [β = -0.009 mmol/L (95% CI: -0.013, -0.005), P < 0.0001] and insulin [-0.020 ln-pmol/L (95% CI: -0.024, -0.017), P < 0.0001]. No magnesium-related SNP or interaction between any SNP and magnesium reached significance after correction for multiple testing. However, rs2274924 in magnesium transporter-encoding TRPM6 showed a nominal association (uncorrected P = 0.03) with glucose, and rs11558471 in SLC30A8 and rs3740393 near CNNM2 showed a nominal interaction (uncorrected, both P = 0.02) with magnesium on glucose. Consistent with other studies, a higher magnesium intake was associated with lower fasting glucose and insulin. Nominal evidence of TRPM6 influence and magnesium interaction with select loci suggests that further investigation is warranted.
10aBlood Glucose10aFemale10aGenetic Loci10aHumans10aInsulin10aMagnesium10aMale10aPolymorphism, Single Nucleotide10aTrace Elements10aTRPM Cation Channels1 aHruby, Adela1 aNgwa, Julius, S1 aRenstrom, Frida1 aWojczynski, Mary, K1 aGanna, Andrea1 aHallmans, Göran1 aHouston, Denise, K1 aJacques, Paul, F1 aKanoni, Stavroula1 aLehtimäki, Terho1 aLemaitre, Rozenn, N1 aManichaikul, Ani1 aNorth, Kari, E1 aNtalla, Ioanna1 aSonestedt, Emily1 aTanaka, Toshiko1 avan Rooij, Frank, J A1 aBandinelli, Stefania1 aDjoussé, Luc1 aGrigoriou, Efi1 aJohansson, Ingegerd1 aLohman, Kurt, K1 aPankow, James, S1 aRaitakari, Olli, T1 aRiserus, Ulf1 aYannakoulia, Mary1 aZillikens, Carola, M1 aHassanali, Neelam1 aLiu, Yongmei1 aMozaffarian, Dariush1 aPapoutsakis, Constantina1 aSyvänen, Ann-Christine1 aUitterlinden, André, G1 aViikari, Jorma1 aGroves, Christopher, J1 aHofman, Albert1 aLind, Lars1 aMcCarthy, Mark, I1 aMikkilä, Vera1 aMukamal, Kenneth1 aFranco, Oscar, H1 aBorecki, Ingrid, B1 aCupples, Adrienne, L1 aDedoussis, George, V1 aFerrucci, Luigi1 aHu, Frank, B1 aIngelsson, Erik1 aKähönen, Mika1 aKao, Linda, W H1 aKritchevsky, Stephen, B1 aOrho-Melander, Marju1 aProkopenko, Inga1 aRotter, Jerome, I1 aSiscovick, David, S1 aWitteman, Jacqueline, C M1 aFranks, Paul, W1 aMeigs, James, B1 aMcKeown, Nicola, M1 aNettleton, Jennifer, A uhttps://chs-nhlbi.org/node/587903716nas a2200577 4500008004100000022001400041245012600055210006900181260001600250300001200266490000800278520196800286653001502254653003102269653002802300653004202328653004202370653003102412653001102443653002202454653003802476653001302514653001102527653002502538653000902563653001802572653001602590653002602606653001402632653003602646653001702682653002402699653002702723100002302750700002002773700001902793700002102812700002002833700001902853700002502872700002902897700001902926700001802945700002202963700002102985700002003006700002103026700002503047700003003072856003603102 2013 eng d a1524-453900aResequencing and clinical associations of the 9p21.3 region: a comprehensive investigation in the Framingham heart study.0 aResequencing and clinical associations of the 9p213 region a com c2013 Feb 19 a799-8100 v1273 aBACKGROUND: 9p21.3 is among the most strongly replicated regions for cardiovascular disease. There are few reports of sequencing the associated 9p21.3 interval. We set out to sequence the 9p21.3 region followed by a comprehensive study of genetic associations with clinical and subclinical cardiovascular disease and its risk factors, as well as with copy number variation and gene expression, in the Framingham Heart Study (FHS).
METHODS AND RESULTS: We sequenced 281 individuals (94 with myocardial infarction, 94 with high coronary artery calcium levels, and 93 control subjects free of elevated coronary artery calcium or myocardial infarction), followed by genotyping and association in >7000 additional FHS individuals. We assessed genetic associations with clinical and subclinical cardiovascular disease, risk factor phenotypes, and gene expression levels of the protein-coding genes CDKN2A and CDKN2B and the noncoding gene ANRIL in freshly harvested leukocytes and platelets. Within this large sample, we found strong associations of 9p21.3 variants with increased risk for myocardial infarction, higher coronary artery calcium levels, and larger abdominal aorta diameters and no evidence for association with traditional cardiovascular disease risk factors. No common protein-coding variation, variants in splice donor or acceptor sites, or copy number variation events were observed. By contrast, strong associations were observed between genetic variants and gene expression, particularly for a short isoform of ANRIL and for CDKN2B.
CONCLUSIONS: Our thorough genomic characterization of 9p21.3 suggests common variants likely account for observed disease associations and provides further support for the hypothesis that complex regulatory variation affecting ANRIL and CDKN2B gene expression may contribute to increased risk for clinically apparent and subclinical coronary artery disease and aortic disease.
10aCalcinosis10aChromosomes, Human, Pair 910aCoronary Artery Disease10aCyclin-Dependent Kinase Inhibitor p1510aCyclin-Dependent Kinase Inhibitor p1610aDNA Copy Number Variations10aFemale10aFollow-Up Studies10aGenetic Predisposition to Disease10aGenotype10aHumans10aLongitudinal Studies10aMale10aMassachusetts10aMiddle Aged10aMyocardial Infarction10aPhenotype10aPolymorphism, Single Nucleotide10aRisk Factors10aRNA, Long Noncoding10aSequence Analysis, DNA1 aJohnson, Andrew, D1 aHwang, Shih-Jen1 aVoorman, Arend1 aMorrison, Alanna1 aPeloso, Gina, M1 aHsu, Yi-Hsiang1 aThanassoulis, George1 aNewton-Cheh, Christopher1 aRogers, Ian, S1 aHoffmann, Udo1 aFreedman, Jane, E1 aFox, Caroline, S1 aPsaty, Bruce, M1 aBoerwinkle, Eric1 aCupples, Adrienne, L1 aO'Donnell, Christopher, J uhttps://chs-nhlbi.org/node/607411004nas a2203505 4500008004100000022001400041245014700055210006900202260001300271300001300284490000600297520115200303653001801455653001601473653002001489653001601509653003001525653001101555653001701566653001801583653003401601653001101635653000901646653003601655653002401691653002401715653002001739100002301759700002301782700002101805700002101826700002101847700001901868700002801887700001601915700001801931700001601949700003101965700002101996700003002017700001802047700001502065700002102080700002302101700001902124700002002143700001902163700002202182700002002204700001802224700003202242700002502274700003002299700002302329700001902352700001902371700002202390700002202412700001902434700001802453700001902471700002202490700002302512700002302535700002202558700002402580700002102604700002202625700002202647700002602669700002302695700002202718700002302740700002402763700002202787700002202809700001202831700002502843700001802868700002802886700002402914700001802938700002502956700001902981700001603000700001903016700001903035700002503054700002503079700002603104700001903130700002003149700001703169700002403186700002003210700002303230700001603253700002003269700002203289700002803311700002103339700002403360700002003384700002303404700001803427700002203445700002103467700001903488700002603507700002203533700002803555700002003583700002803603700002703631700002003658700002303678700002003701700002103721700002403742700002003766700001503786700002803801700002603829700001903855700002803874700001903902700002503921700002403946700002703970700002003997700001404017700002004031700002204051700001904073700001804092700001804110700002104128700002004149700002204169700001604191700002204207700002204229700002604251700002604277700001704303700002004320700002304340700001904363700002304382700002004405700002304425700001904448700001804467700002304485700002504508700001904533700001904552700002004571700003004591700003504621700002104656700001704677700002104694700001904715700002504734700002404759700001804783700001504801700002404816700002204840700002504862700001504887700002304902700002004925700001904945700002204964700002004986700001805006700002205024700002005046700002105066700002105087700001705108700002105125700002005146700001605166700002105182700001905203700002505222700002405247700002305271700001905294700002205313700001805335700002005353700002005373700001905393700002105412700002405433700001805457700002005475700002105495700002005516700002505536700002105561700002105582700002405603700001805627700001605645700002105661700003705682700002205719700001805741700002005759700002105779700002005800700002605820700002305846700001905869700002005888700002305908700002405931700002005955700001905975700002005994700002406014700002506038700001906063700002106082700002106103700001806124700002106142700003006163700002006193700002306213700002206236700002006258700002806278700002206306700001906328700002406347700002206371700002006393700001906413700002306432700001506455700001706470700001506487700001806502700001906520700002706539700002306566700002206589700002106611700002206632700002206654700002306676700002506699700002106724700001906745700001806764700001906782700002106801700001906822700001806841700002906859700001906888700002106907700002306928700002006951700002106971700002206992700001907014700002307033700001807056700002007074700001907094700002107113700002607134700002407160700002307184700002107207700002307228700002507251700002207276700002407298700001107322700002007333700002507353700001907378700001807397710002307415710002407438856003607462 2013 eng d a1553-740400aSex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits.0 aSexstratified genomewide association studies including 270000 in c2013 Jun ae10035000 v93 aGiven the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
10aAnthropometry10aBody Height10aBody Mass Index10aBody Weight10aBody Weights and Measures10aFemale10aGenetic Loci10aGenome, Human10aGenome-Wide Association Study10aHumans10aMale10aPolymorphism, Single Nucleotide10aSex Characteristics10aWaist Circumference10aWaist-Hip Ratio1 aRandall, Joshua, C1 aWinkler, Thomas, W1 aKutalik, Zoltán1 aBerndt, Sonja, I1 aJackson, Anne, U1 aMonda, Keri, L1 aKilpeläinen, Tuomas, O1 aEsko, Tõnu1 aMägi, Reedik1 aLi, Shengxu1 aWorkalemahu, Tsegaselassie1 aFeitosa, Mary, F1 aCroteau-Chonka, Damien, C1 aDay, Felix, R1 aFall, Tove1 aFerreira, Teresa1 aGustafsson, Stefan1 aLocke, Adam, E1 aMathieson, Iain1 aScherag, Andre1 aVedantam, Sailaja1 aWood, Andrew, R1 aLiang, Liming1 aSteinthorsdottir, Valgerdur1 aThorleifsson, Gudmar1 aDermitzakis, Emmanouil, T1 aDimas, Antigone, S1 aKarpe, Fredrik1 aMin, Josine, L1 aNicholson, George1 aClegg, Deborah, J1 aPerson, Thomas1 aKrohn, Jon, P1 aBauer, Sabrina1 aBuechler, Christa1 aEisinger, Kristina1 aBonnefond, Amélie1 aFroguel, Philippe1 aHottenga, Jouke-Jan1 aProkopenko, Inga1 aWaite, Lindsay, L1 aHarris, Tamara, B1 aSmith, Albert, Vernon1 aShuldiner, Alan, R1 aMcArdle, Wendy, L1 aCaulfield, Mark, J1 aMunroe, Patricia, B1 aGrönberg, Henrik1 aChen, Yii-Der Ida1 aLi, Guo1 aBeckmann, Jacques, S1 aJohnson, Toby1 aThorsteinsdottir, Unnur1 aTeder-Laving, Maris1 aKhaw, Kay-Tee1 aWareham, Nicholas, J1 aZhao, Jing Hua1 aAmin, Najaf1 aOostra, Ben, A1 aKraja, Aldi, T1 aProvince, Michael, A1 aCupples, Adrienne, L1 aHeard-Costa, Nancy, L1 aKaprio, Jaakko1 aRipatti, Samuli1 aSurakka, Ida1 aCollins, Francis, S1 aSaramies, Jouko1 aTuomilehto, Jaakko1 aJula, Antti1 aSalomaa, Veikko1 aErdmann, Jeanette1 aHengstenberg, Christian1 aLoley, Christina1 aSchunkert, Heribert1 aLamina, Claudia1 aWichmann, Erich, H1 aAlbrecht, Eva1 aGieger, Christian1 aHicks, Andrew, A1 aJohansson, Asa1 aPramstaller, Peter, P1 aKathiresan, Sekar1 aSpeliotes, Elizabeth, K1 aPenninx, Brenda1 aHartikainen, Anna-Liisa1 aJarvelin, Marjo-Riitta1 aGyllensten, Ulf1 aBoomsma, Dorret, I1 aCampbell, Harry1 aWilson, James, F1 aChanock, Stephen, J1 aFarrall, Martin1 aGoel, Anuj1 aMedina-Gómez, Carolina1 aRivadeneira, Fernando1 aEstrada, Karol1 aUitterlinden, André, G1 aHofman, Albert1 aZillikens, Carola, M1 aHeijer, Martin, den1 aKiemeney, Lambertus, A1 aMaschio, Andrea1 aHall, Per1 aTyrer, Jonathan1 aTeumer, Alexander1 aVölzke, Henry1 aKovacs, Peter1 aTönjes, Anke1 aMangino, Massimo1 aSpector, Tim, D1 aHayward, Caroline1 aRudan, Igor1 aHall, Alistair, S1 aSamani, Nilesh, J1 aAttwood, Antony, Paul1 aSambrook, Jennifer, G1 aHung, Joseph1 aPalmer, Lyle, J1 aLokki, Marja-Liisa1 aSinisalo, Juha1 aBoucher, Gabrielle1 aHuikuri, Heikki1 aLorentzon, Mattias1 aOhlsson, Claes1 aEklund, Niina1 aEriksson, Johan, G1 aBarlassina, Cristina1 aRivolta, Carlo1 aNolte, Ilja, M1 aSnieder, Harold1 avan der Klauw, Melanie, M1 avan Vliet-Ostaptchouk, Jana, V1 aGejman, Pablo, V1 aShi, Jianxin1 aJacobs, Kevin, B1 aWang, Zhaoming1 aBakker, Stephan, J L1 aLeach, Irene, Mateo1 aNavis, Gerjan1 aHarst, Pim1 aMartin, Nicholas, G1 aMedland, Sarah, E1 aMontgomery, Grant, W1 aYang, Jian1 aChasman, Daniel, I1 aRidker, Paul, M1 aRose, Lynda, M1 aLehtimäki, Terho1 aRaitakari, Olli1 aAbsher, Devin1 aIribarren, Carlos1 aBasart, Hanneke1 aHovingh, Kees, G1 aHyppönen, Elina1 aPower, Chris1 aAnderson, Denise1 aBeilby, John, P1 aHui, Jennie1 aJolley, Jennifer1 aSager, Hendrik1 aBornstein, Stefan, R1 aSchwarz, Peter, E H1 aKristiansson, Kati1 aPerola, Markus1 aLindström, Jaana1 aSwift, Amy, J1 aUusitupa, Matti1 aAtalay, Mustafa1 aLakka, Timo, A1 aRauramaa, Rainer1 aBolton, Jennifer, L1 aFowkes, Gerry1 aFraser, Ross, M1 aPrice, Jackie, F1 aFischer, Krista1 aKov, Kaarel, Krjutå1 aMetspalu, Andres1 aMihailov, Evelin1 aLangenberg, Claudia1 aLuan, Jian'an1 aOng, Ken, K1 aChines, Peter, S1 aKeinanen-Kiukaanniemi, Sirkka, M1 aSaaristo, Timo, E1 aEdkins, Sarah1 aFranks, Paul, W1 aHallmans, Göran1 aShungin, Dmitry1 aMorris, Andrew, David1 aPalmer, Colin, N A1 aErbel, Raimund1 aMoebus, Susanne1 aNöthen, Markus, M1 aPechlivanis, Sonali1 aHveem, Kristian1 aNarisu, Narisu1 aHamsten, Anders1 aHumphries, Steve, E1 aStrawbridge, Rona, J1 aTremoli, Elena1 aGrallert, Harald1 aThorand, Barbara1 aIllig, Thomas1 aKoenig, Wolfgang1 aMüller-Nurasyid, Martina1 aPeters, Annette1 aBoehm, Bernhard, O1 aKleber, Marcus, E1 aMärz, Winfried1 aWinkelmann, Bernhard, R1 aKuusisto, Johanna1 aLaakso, Markku1 aArveiler, Dominique1 aCesana, Giancarlo1 aKuulasmaa, Kari1 aVirtamo, Jarmo1 aYarnell, John, W G1 aKuh, Diana1 aWong, Andrew1 aLind, Lars1 ade Faire, Ulf1 aGigante, Bruna1 aMagnusson, Patrik, K E1 aPedersen, Nancy, L1 aDedoussis, George1 aDimitriou, Maria1 aKolovou, Genovefa1 aKanoni, Stavroula1 aStirrups, Kathleen1 aBonnycastle, Lori, L1 aNjølstad, Inger1 aWilsgaard, Tom1 aGanna, Andrea1 aRehnberg, Emil1 aHingorani, Aroon1 aKivimaki, Mika1 aKumari, Meena1 aAssimes, Themistocles, L1 aBarroso, Inês1 aBoehnke, Michael1 aBorecki, Ingrid, B1 aDeloukas, Panos1 aFox, Caroline, S1 aFrayling, Timothy1 aGroop, Leif, C1 aHaritunians, Talin1 aHunter, David1 aIngelsson, Erik1 aKaplan, Robert1 aMohlke, Karen, L1 aO'Connell, Jeffrey, R1 aSchlessinger, David1 aStrachan, David, P1 aStefansson, Kari1 aDuijn, Cornelia, M1 aAbecasis, Goncalo, R1 aMcCarthy, Mark, I1 aHirschhorn, Joel, N1 aQi, Lu1 aLoos, Ruth, J F1 aLindgren, Cecilia, M1 aNorth, Kari, E1 aHeid, Iris, M1 aDIAGRAM Consortium1 aMAGIC investigators uhttps://chs-nhlbi.org/node/602802102nas a2200469 4500008004100000022001400041245008200055210006900137260001300206300001200219490000700231520073300238653002100971653002600992653002301018653002201041653001801063653003401081653001301115653001701128653001101145653002401156100002401180700001901204700002301223700001801246700001201264700001801276700001701294700001301311700001801324700001901342700001601361700001901377700003001396700002001426700002501446700001901471700002101490710008501511856003601596 2013 eng d a1546-171800aWhole-genome sequence-based analysis of high-density lipoprotein cholesterol.0 aWholegenome sequencebased analysis of highdensity lipoprotein ch c2013 Aug a899-9010 v453 aWe describe initial steps for interrogating whole-genome sequence data to characterize the genetic architecture of a complex trait, levels of high-density lipoprotein cholesterol (HDL-C). We report whole-genome sequencing and analysis of 962 individuals from the Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) studies. From this analysis, we estimate that common variation contributes more to heritability of HDL-C levels than rare variation, and screening for mendelian variants for dyslipidemia identified individuals with extreme HDL-C levels. Whole-genome sequencing analyses highlight the value of regulatory and non-protein-coding regions of the genome in addition to protein-coding regions.
10aCholesterol, HDL10aComputational Biology10aDatabases, Genetic10aGenetic Variation10aGenome, Human10aGenome-Wide Association Study10aGenomics10aHeterozygote10aHumans10aOpen Reading Frames1 aMorrison, Alanna, C1 aVoorman, Arend1 aJohnson, Andrew, D1 aLiu, Xiaoming1 aYu, Jin1 aLi, Alexander1 aMuzny, Donna1 aYu, Fuli1 aRice, Kenneth1 aZhu, Chengsong1 aBis, Joshua1 aHeiss, Gerardo1 aO'Donnell, Christopher, J1 aPsaty, Bruce, M1 aCupples, Adrienne, L1 aGibbs, Richard1 aBoerwinkle, Eric1 aCohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium uhttps://chs-nhlbi.org/node/628308212nas a2202197 4500008004100000022001400041245013100055210006900186260001600255300001000271490000800281520207900289653001002368653000902378653002602387653002102413653001502434653002102449653001102470653002002481653001302501653001102514653000902525653003702534653001602571653002402587653003602611653001102647100002302658700002202681700001902703700002702722700001502749700001402764700002502778700001902803700002002822700001702842700002002859700001902879700002502898700001702923700002002940700002102960700002202981700002503003700001903028700002403047700002603071700002803097700001703125700001603142700003103158700001503189700002003204700002103224700001803245700002003263700001903283700002403302700002003326700002103346700001803367700002103385700002003406700001903426700002103445700001903466700001803485700002803503700002103531700002503552700001503577700002303592700001903615700002703634700002403661700002403685700002403709700001803733700002103751700001603772700002603788700002303814700001503837700002103852700002303873700002403896700001803920700002603938700002203964700001903986700001804005700001804023700002104041700001904062700001704081700002104098700001904119700002104138700002404159700002404183700003404207700002004241700002204261700002504283700001904308700002104327700001904348700001804367700002004385700002004405700001504425700001904440700002804459700002004487700001404507700002104521700002404542700002504566700001804591700002004609700002804629700002204657700002304679700001504702700002504717700002904742700003104771700002204802700002204824700002204846700002004868700002304888700001804911700002004929700001904949700001904968700002504987700002205012700002005034700002405054700002305078700001805101700002505119700002405144700002005168700001905188700001805207700001505225700002205240700002505262700002005287700002105307700002105328700001905349700002305368700002205391700002205413700002205435700002105457700002505478700001905503700002705522700001905549700002205568700002005590700002505610700002105635700002005656700002105676700002105697700002005718700002405738700002805762700001805790700001905808700002405827700001905851700002005870700002405890700002105914700001905935710002405954856003605978 2014 eng d a1756-183300aAssociation between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data.0 aAssociation between alcohol and cardiovascular disease Mendelian c2014 Jul 10 ag41640 v3493 aOBJECTIVE: To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease.
DESIGN: Mendelian randomisation meta-analysis of 56 epidemiological studies.
PARTICIPANTS: 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers.
MAIN OUTCOME MEASURES: Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption.
RESULTS: Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)).
CONCLUSIONS: Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health.
10aAdult10aAged10aAlcohol Dehydrogenase10aAlcohol Drinking10aBiomarkers10aCoronary Disease10aFemale10aGenetic Markers10aGenotype10aHumans10aMale10aMendelian Randomization Analysis10aMiddle Aged10aModels, Statistical10aPolymorphism, Single Nucleotide10aStroke1 aHolmes, Michael, V1 aDale, Caroline, E1 aZuccolo, Luisa1 aSilverwood, Richard, J1 aGuo, Yiran1 aYe, Zheng1 aPrieto-Merino, David1 aDehghan, Abbas1 aTrompet, Stella1 aWong, Andrew1 aCavadino, Alana1 aDrogan, Dagmar1 aPadmanabhan, Sandosh1 aLi, Shanshan1 aYesupriya, Ajay1 aLeusink, Maarten1 aSundström, Johan1 aHubacek, Jaroslav, A1 aPikhart, Hynek1 aSwerdlow, Daniel, I1 aPanayiotou, Andrie, G1 aBorinskaya, Svetlana, A1 aFinan, Chris1 aShah, Sonia1 aKuchenbaecker, Karoline, B1 aShah, Tina1 aEngmann, Jorgen1 aFolkersen, Lasse1 aEriksson, Per1 aRicceri, Fulvio1 aMelander, Olle1 aSacerdote, Carlotta1 aGamble, Dale, M1 aRayaprolu, Sruti1 aRoss, Owen, A1 aMcLachlan, Stela1 aVikhireva, Olga1 aSluijs, Ivonne1 aScott, Robert, A1 aAdamkova, Vera1 aFlicker, Leon1 avan Bockxmeer, Frank, M1 aPower, Christine1 aMarques-Vidal, Pedro1 aMeade, Tom1 aMarmot, Michael, G1 aFerro, Jose, M1 aPaulos-Pinheiro, Sofia1 aHumphries, Steve, E1 aTalmud, Philippa, J1 aLeach, Irene, Mateo1 aVerweij, Niek1 aLinneberg, Allan1 aSkaaby, Tea1 aDoevendans, Pieter, A1 aCramer, Maarten, J1 aHarst, Pim1 aKlungel, Olaf, H1 aDowling, Nicole, F1 aDominiczak, Anna, F1 aKumari, Meena1 aNicolaides, Andrew, N1 aWeikert, Cornelia1 aBoeing, Heiner1 aEbrahim, Shah1 aGaunt, Tom, R1 aPrice, Jackie, F1 aLannfelt, Lars1 aPeasey, Anne1 aKubinova, Ruzena1 aPajak, Andrzej1 aMalyutina, Sofia1 aVoevoda, Mikhail, I1 aTamosiunas, Abdonas1 avan der Zee, Anke, H Maitland1 aNorman, Paul, E1 aHankey, Graeme, J1 aBergmann, Manuela, M1 aHofman, Albert1 aFranco, Oscar, H1 aCooper, Jackie1 aPalmen, Jutta1 aSpiering, Wilko1 ade Jong, Pim, A1 aKuh, Diana1 aHardy, Rebecca1 aUitterlinden, André, G1 aIkram, Arfan, M1 aFord, Ian1 aHyppönen, Elina1 aAlmeida, Osvaldo, P1 aWareham, Nicholas, J1 aKhaw, Kay-Tee1 aHamsten, Anders1 aHusemoen, Lise, Lotte N1 aTjønneland, Anne1 aTolstrup, Janne, S1 aRimm, Eric1 aBeulens, Joline, W J1 aVerschuren, W, M Monique1 aOnland-Moret, Charlotte, N1 aHofker, Marten, H1 aWannamethee, Goya1 aWhincup, Peter, H1 aMorris, Richard1 aVicente, Astrid, M1 aWatkins, Hugh1 aFarrall, Martin1 aJukema, Wouter1 aMeschia, James1 aCupples, Adrienne, L1 aSharp, Stephen, J1 aFornage, Myriam1 aKooperberg, Charles1 aLaCroix, Andrea, Z1 aDai, James, Y1 aLanktree, Matthew, B1 aSiscovick, David, S1 aJorgenson, Eric1 aSpring, Bonnie1 aCoresh, Josef1 aLi, Yun, R1 aBuxbaum, Sarah, G1 aSchreiner, Pamela, J1 aEllison, Curtis1 aTsai, Michael, Y1 aPatel, Sanjay, R1 aRedline, Susan1 aJohnson, Andrew, D1 aHoogeveen, Ron, C1 aHakonarson, Hakon1 aRotter, Jerome, I1 aBoerwinkle, Eric1 ade Bakker, Paul, I W1 aKivimaki, Mika1 aAsselbergs, Folkert, W1 aSattar, Naveed1 aLawlor, Debbie, A1 aWhittaker, John1 aSmith, George, Davey1 aMukamal, Kenneth1 aPsaty, Bruce, M1 aWilson, James, G1 aLange, Leslie, A1 aHamidovic, Ajna1 aHingorani, Aroon, D1 aNordestgaard, Børge, G1 aBobak, Martin1 aLeon, David, A1 aLangenberg, Claudia1 aPalmer, Tom, M1 aReiner, Alex, P1 aKeating, Brendan, J1 aDudbridge, Frank1 aCasas, Juan, P1 aInterAct Consortium uhttps://chs-nhlbi.org/node/656905943nas a2201657 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2014 eng d a1537-660500aAssociation of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks.0 aAssociation of lowfrequency and rare codingsequence variants wit c2014 Feb 06 a223-320 v943 aLow-frequency coding DNA sequence variants in the proprotein convertase subtilisin/kexin type 9 gene (PCSK9) lower plasma low-density lipoprotein cholesterol (LDL-C), protect against risk of coronary heart disease (CHD), and have prompted the development of a new class of therapeutics. It is uncertain whether the PCSK9 example represents a paradigm or an isolated exception. We used the "Exome Array" to genotype >200,000 low-frequency and rare coding sequence variants across the genome in 56,538 individuals (42,208 European ancestry [EA] and 14,330 African ancestry [AA]) and tested these variants for association with LDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides. Although we did not identify new genes associated with LDL-C, we did identify four low-frequency (frequencies between 0.1% and 2%) variants (ANGPTL8 rs145464906 [c.361C>T; p.Gln121*], PAFAH1B2 rs186808413 [c.482C>T; p.Ser161Leu], COL18A1 rs114139997 [c.331G>A; p.Gly111Arg], and PCSK7 rs142953140 [c.1511G>A; p.Arg504His]) with large effects on HDL-C and/or triglycerides. None of these four variants was associated with risk for CHD, suggesting that examples of low-frequency coding variants with robust effects on both lipids and CHD will be limited.
10a1-Alkyl-2-acetylglycerophosphocholine Esterase10aAdult10aAfrican Continental Ancestry Group10aAged10aAlleles10aAnimals10aCholesterol, HDL10aCholesterol, LDL10aCohort Studies10aCoronary Disease10aEuropean Continental Ancestry Group10aFemale10aGene Frequency10aGenetic Association Studies10aGenetic Code10aGenetic Variation10aHumans10aLinear Models10aMale10aMice10aMice, Inbred C57BL10aMicrotubule-Associated Proteins10aMiddle Aged10aPhenotype10aSequence Analysis, DNA10aSubtilisins10aTriglycerides1 aPeloso, Gina, M1 aAuer, Paul, L1 aBis, Joshua, C1 aVoorman, Arend1 aMorrison, Alanna, C1 aStitziel, Nathan, O1 aBrody, Jennifer, A1 aKhetarpal, Sumeet, A1 aCrosby, Jacy, R1 aFornage, Myriam1 aIsaacs, Aaron1 aJakobsdottir, Johanna1 aFeitosa, Mary, F1 aDavies, Gail1 aHuffman, Jennifer, E1 aManichaikul, Ani1 aDavis, Brian1 aLohman, Kurt1 aJoon, Aron, Y1 aSmith, Albert, V1 aGrove, Megan, L1 aZanoni, Paolo1 aRedon, Valeska1 aDemissie, Serkalem1 aLawson, Kim1 aPeters, Ulrike1 aCarlson, Christopher1 aJackson, Rebecca, D1 aRyckman, Kelli, K1 aMackey, Rachel, H1 aRobinson, Jennifer, G1 aSiscovick, David, S1 aSchreiner, Pamela, J1 aMychaleckyj, Josyf, C1 aPankow, James, S1 aHofman, Albert1 aUitterlinden, André, G1 aHarris, Tamara, B1 aTaylor, Kent, D1 aStafford, Jeanette, M1 aReynolds, Lindsay, M1 aMarioni, Riccardo, E1 aDehghan, Abbas1 aFranco, Oscar, H1 aPatel, Aniruddh, P1 aLu, Yingchang1 aHindy, George1 aGottesman, Omri1 aBottinger, Erwin, P1 aMelander, Olle1 aOrho-Melander, Marju1 aLoos, Ruth, J F1 aDuga, Stefano1 aMerlini, Piera, Angelica1 aFarrall, Martin1 aGoel, Anuj1 aAsselta, Rosanna1 aGirelli, Domenico1 aMartinelli, Nicola1 aShah, Svati, H1 aKraus, William, E1 aLi, Mingyao1 aRader, Daniel, J1 aReilly, Muredach, P1 aMcPherson, Ruth1 aWatkins, Hugh1 aArdissino, Diego1 aZhang, Qunyuan1 aWang, Judy1 aTsai, Michael, Y1 aTaylor, Herman, A1 aCorrea, Adolfo1 aGriswold, Michael, E1 aLange, Leslie, A1 aStarr, John, M1 aRudan, Igor1 aEiriksdottir, Gudny1 aLauner, Lenore, J1 aOrdovas, Jose, M1 aLevy, Daniel1 aChen, Y-D, Ida1 aReiner, Alexander, P1 aHayward, Caroline1 aPolasek, Ozren1 aDeary, Ian, J1 aBorecki, Ingrid, B1 aLiu, Yongmei1 aGudnason, Vilmundur1 aWilson, James, G1 aDuijn, Cornelia, M1 aKooperberg, Charles1 aRich, Stephen, S1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aO'Donnell, Christopher, J1 aRice, Kenneth1 aBoerwinkle, Eric1 aKathiresan, Sekar1 aCupples, Adrienne, L1 aNHLBI GO Exome Sequencing Project uhttps://chs-nhlbi.org/node/659003125nas a2200553 4500008004100000022001400041245011100055210006900166260000900235300001200244490000600256520150100262653002101763653001101784653003401795653001101829653000901840653001601849653003601865100003001901700002901931700002001960700002201980700002102002700002202023700002202045700002402067700001202091700002302103700001902126700002202145700001802167700001902185700001902204700002602223700002802249700002102277700002802298700002402326700002002350700002502370700002702395700002002422700001802442700002802460700002402488700002302512856003602535 2014 eng d a1932-620300aThe challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels.0 achallenges of genomewide interaction studies lessons to learn fr c2014 ae1092900 v93 aGenome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.
10aCholesterol, HDL10aFemale10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide1 avan Leeuwen, Elisabeth, M1 aSmouter, Françoise, A S1 aKam-Thong, Tony1 aKarbalai, Nazanin1 aSmith, Albert, V1 aHarris, Tamara, B1 aLauner, Lenore, J1 aSitlani, Colleen, M1 aLi, Guo1 aBrody, Jennifer, A1 aBis, Joshua, C1 aWhite, Charles, C1 aJaiswal, Alok1 aOostra, Ben, A1 aHofman, Albert1 aRivadeneira, Fernando1 aUitterlinden, André, G1 aBoerwinkle, Eric1 aBallantyne, Christie, M1 aGudnason, Vilmundur1 aPsaty, Bruce, M1 aCupples, Adrienne, L1 aJarvelin, Marjo-Riitta1 aRipatti, Samuli1 aIsaacs, Aaron1 aMüller-Myhsok, Bertram1 aKarssen, Lennart, C1 aDuijn, Cornelia, M uhttps://chs-nhlbi.org/node/660706392nas a2201669 4500008004100000022001400041245009700055210006900152260001600221300001200237490000700249520182200256653001002078653002202088653000902110653001202119653003702131653002002168653002602188653001702214653002102231653001802252653004002270653001102310653001902321653001102340653000902351653001602360653001202376653003602388653001302424100001402437700002802451700002002479700002002499700002002519700001902539700002102558700001902579700002002598700001802618700002302636700001802659700001802677700001602695700002402711700001202735700003202747700002302779700001502802700001902817700002002836700001902856700002502875700001702900700002302917700002202940700002302962700002202985700001503007700002503022700002703047700002003074700002203094700002403116700001203140700002103152700002103173700002103194700002503215700001903240700002003259700001903279700002603298700002103324700001703345700002403362700001703386700002303403700002103426700001603447700001803463700002503481700002003506700002003526700002103546700001903567700002303586700001903609700002403628700002303652700002203675700001803697700001803715700002303733700001703756700001203773700001703785700002003802700001703822700001903839700002503858700001603883700001903899700002003918700002003938700002303958700002203981700002804003700002504031700002104056700001604077700001804093700002404111700001504135700002904150700002404179700002504203700003004228700001504258700002004273700001704293700001804310700002204328700002004350700002304370700002104393700002104414700002004435700002504455700002004480700002504500700001404525700002304539700002004562700002904582700001704611700002004628700002704648700001104675856003604686 2014 eng d a1460-208300aFTO genetic variants, dietary intake and body mass index: insights from 177,330 individuals.0 aFTO genetic variants dietary intake and body mass index insights c2014 Dec 20 a6961-720 v233 aFTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177,330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m(2), P = 1.9 × 10(-105)), and all participants (0.30 [0.30, 0.35] kg/m(2), P = 3.6 × 10(-107)). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10(-16)), and relative weak associations with lower total energy intake (-6.4 [-10.1, -2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (-0.07 [-0.11, -0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10(-9)) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity.
10aAdult10aAfrican Americans10aAged10aAlleles10aAsian Continental Ancestry Group10aBody Mass Index10aDietary Carbohydrates10aDietary Fats10aDietary Proteins10aEnergy Intake10aEuropean Continental Ancestry Group10aFemale10aGene Frequency10aHumans10aMale10aMiddle Aged10aObesity10aPolymorphism, Single Nucleotide10aProteins1 aQi, Qibin1 aKilpeläinen, Tuomas, O1 aDowner, Mary, K1 aTanaka, Toshiko1 aSmith, Caren, E1 aSluijs, Ivonne1 aSonestedt, Emily1 aChu, Audrey, Y1 aRenstrom, Frida1 aLin, Xiaochen1 aÄngquist, Lars, H1 aHuang, Jinyan1 aLiu, Zhonghua1 aLi, Yanping1 aAli, Muhammad, Asif1 aXu, Min1 aAhluwalia, Tarunveer, Singh1 aBoer, Jolanda, M A1 aChen, Peng1 aDaimon, Makoto1 aEriksson, Johan1 aPerola, Markus1 aFriedlander, Yechiel1 aGao, Yu-Tang1 aHeppe, Denise, H M1 aHolloway, John, W1 aHouston, Denise, K1 aKanoni, Stavroula1 aKim, Yu-Mi1 aLaaksonen, Maarit, A1 aJääskeläinen, Tiina1 aLee, Nanette, R1 aLehtimäki, Terho1 aLemaitre, Rozenn, N1 aLu, Wei1 aLuben, Robert, N1 aManichaikul, Ani1 aMännistö, Satu1 aMarques-Vidal, Pedro1 aMonda, Keri, L1 aNgwa, Julius, S1 aPerusse, Louis1 avan Rooij, Frank, J A1 aXiang, Yong-Bing1 aWen, Wanqing1 aWojczynski, Mary, K1 aZhu, Jingwen1 aBorecki, Ingrid, B1 aBouchard, Claude1 aCai, Qiuyin1 aCooper, Cyrus1 aDedoussis, George, V1 aDeloukas, Panos1 aFerrucci, Luigi1 aForouhi, Nita, G1 aHansen, Torben1 aChristiansen, Lene1 aHofman, Albert1 aJohansson, Ingegerd1 aJørgensen, Torben1 aKarasawa, Shigeru1 aKhaw, Kay-Tee1 aKim, Mi-Kyung1 aKristiansson, Kati1 aLi, Huaixing1 aLin, Xu1 aLiu, Yongmei1 aLohman, Kurt, K1 aLong, Jirong1 aMikkilä, Vera1 aMozaffarian, Dariush1 aNorth, Kari1 aPedersen, Oluf1 aRaitakari, Olli1 aRissanen, Harri1 aTuomilehto, Jaakko1 aSchouw, Yvonne, T1 aUitterlinden, André, G1 aZillikens, Carola, M1 aFranco, Oscar, H1 aTai, Shyong1 aShu, Xiao, Ou1 aSiscovick, David, S1 aToft, Ulla1 aVerschuren, W, M Monique1 aVollenweider, Peter1 aWareham, Nicholas, J1 aWitteman, Jacqueline, C M1 aZheng, Wei1 aRidker, Paul, M1 aKang, Jae, H1 aLiang, Liming1 aJensen, Majken, K1 aCurhan, Gary, C1 aPasquale, Louis, R1 aHunter, David, J1 aMohlke, Karen, L1 aUusitupa, Matti1 aCupples, Adrienne, L1 aRankinen, Tuomo1 aOrho-Melander, Marju1 aWang, Tao1 aChasman, Daniel, I1 aFranks, Paul, W1 aSørensen, Thorkild, I A1 aHu, Frank, B1 aLoos, Ruth, J F1 aNettleton, Jennifer, A1 aQi, Lu uhttps://chs-nhlbi.org/node/693805734nas a2201333 4500008004100000022001400041245007800055210006900133260001500202300001000217490000800227520196900235653003902204653002502243653002102268653004002289653001002329653001302339653001702352653001102369653001002380653001302390653001702403653002702420653001802447110010402465700001702569700002002586700001802606700002302624700002402647700002102671700001802692700002202710700001402732700001802746700002002764700002302784700002202807700001202829700001302841700001402854700002002868700001602888700001502904700002002919700001802939700002802957700002102985700002203006700002303028700002303051700001203074700001903086700002503105700002103130700002003151700002303171700001803194700002303212700002903235700002303264700002303287700001903310700002003329700001903349700001903368700002203387700002403409700002403433700002303457700002203480700001703502700002203519700002003541700001903561700001903580700002003599700001903619700002603638700002003664700002403684700003003708700002003738700002803758700002203786700002103808700001903829700001803848700002503866700002103891700002003912700002003932700002303952700002203975700002203997700002204019700002004041700002404061700002104085700002404106700002104130700002204151700001604173700002104189700002004210700002604230700002004256700002504276700002004301700002104321700002204342856003604364 2014 eng d a1533-440600aLoss-of-function mutations in APOC3, triglycerides, and coronary disease.0 aLossoffunction mutations in APOC3 triglycerides and coronary dis c2014 Jul 3 a22-310 v3713 aBACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype.
METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons.
RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)).
CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).
10aAfrican Continental Ancestry Group10aApolipoprotein C-III10aCoronary Disease10aEuropean Continental Ancestry Group10aExome10aGenotype10aHeterozygote10aHumans10aLiver10aMutation10aRisk Factors10aSequence Analysis, DNA10aTriglycerides1 aTG and HDL Working Group of the Exome Sequencing Project, National Heart, Lung, and Blood Institute1 aCrosby, Jacy1 aPeloso, Gina, M1 aAuer, Paul, L1 aCrosslin, David, R1 aStitziel, Nathan, O1 aLange, Leslie, A1 aLu, Yingchang1 aTang, Zheng-Zheng1 aZhang, He1 aHindy, George1 aMasca, Nicholas1 aStirrups, Kathleen1 aKanoni, Stavroula1 aDo, Ron1 aJun, Goo1 aHu, Youna1 aKang, Hyun, Min1 aXue, Chenyi1 aGoel, Anuj1 aFarrall, Martin1 aDuga, Stefano1 aMerlini, Pier, Angelica1 aAsselta, Rosanna1 aGirelli, Domenico1 aOlivieri, Oliviero1 aMartinelli, Nicola1 aYin, Wu1 aReilly, Dermot1 aSpeliotes, Elizabeth1 aFox, Caroline, S1 aHveem, Kristian1 aHolmen, Oddgeir, L1 aNikpay, Majid1 aFarlow, Deborah, N1 aAssimes, Themistocles, L1 aFranceschini, Nora1 aRobinson, Jennifer1 aNorth, Kari, E1 aMartin, Lisa, W1 aDePristo, Mark1 aGupta, Namrata1 aEscher, Stefan, A1 aJansson, Jan-Håkan1 aVan Zuydam, Natalie1 aPalmer, Colin, N A1 aWareham, Nicholas1 aKoch, Werner1 aMeitinger, Thomas1 aPeters, Annette1 aLieb, Wolfgang1 aErbel, Raimund1 aKönig, Inke, R1 aKruppa, Jochen1 aDegenhardt, Franziska1 aGottesman, Omri1 aBottinger, Erwin, P1 aO'Donnell, Christopher, J1 aPsaty, Bruce, M1 aBallantyne, Christie, M1 aAbecasis, Goncalo1 aOrdovas, Jose, M1 aMelander, Olle1 aWatkins, Hugh1 aOrho-Melander, Marju1 aArdissino, Diego1 aLoos, Ruth, J F1 aMcPherson, Ruth1 aWiller, Cristen, J1 aErdmann, Jeanette1 aHall, Alistair, S1 aSamani, Nilesh, J1 aDeloukas, Panos1 aSchunkert, Heribert1 aWilson, James, G1 aKooperberg, Charles1 aRich, Stephen, S1 aTracy, Russell, P1 aLin, Dan-Yu1 aAltshuler, David1 aGabriel, Stacey1 aNickerson, Deborah, A1 aJarvik, Gail, P1 aCupples, Adrienne, L1 aReiner, Alex, P1 aBoerwinkle, Eric1 aKathiresan, Sekar uhttps://chs-nhlbi.org/node/660503769nas a2200937 4500008004100000022001400041245009400055210006900149260001600218300001200234490000700246520111800253653002201371653001601393653002301409653004001432653001101472653001701483653002201500653003401522653001101556653001401567653001801581100002501599700001801624700001801642700002501660700002101685700001801706700002301724700002301747700002201770700001201792700002001804700002301824700002201847700002201869700002001891700002801911700002201939700002201961700002001983700002302003700001802026700002802044700001802072700002202090700002202112700001902134700002002153700001702173700002302190700002302213700002202236700002102258700001802279700002202297700002202319700002202341700002002363700002202383700001402405700001502419700002202434700002202456700002402478700002402502700002402526700001702550700002202567700001702589700002102606700002402627700002302651700002502674700002302699700002402722700002402746700002502770856003602795 2014 eng d a1460-208300aMeta-analysis of loci associated with age at natural menopause in African-American women.0 aMetaanalysis of loci associated with age at natural menopause in c2014 Jun 15 a3327-420 v233 aAge at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA.
10aAfrican Americans10aAge Factors10aChromosomes, Human10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenetic Variation10aGenome-Wide Association Study10aHumans10aMenopause10aUnited States1 aChen, Christina, T L1 aLiu, Ching-Ti1 aChen, Gary, K1 aAndrews, Jeanette, S1 aArnold, Alice, M1 aDreyfus, Jill1 aFranceschini, Nora1 aGarcia, Melissa, E1 aKerr, Kathleen, F1 aLi, Guo1 aLohman, Kurt, K1 aMusani, Solomon, K1 aNalls, Michael, A1 aRaffel, Leslie, J1 aSmith, Jennifer1 aAmbrosone, Christine, B1 aBandera, Elisa, V1 aBernstein, Leslie1 aBritton, Angela1 aBrzyski, Robert, G1 aCappola, Anne1 aCarlson, Christopher, S1 aCouper, David1 aDeming, Sandra, L1 aGoodarzi, Mark, O1 aHeiss, Gerardo1 aJohn, Esther, M1 aLu, Xiaoning1 aLe Marchand, Loïc1 aMarciante, Kristin1 aMcKnight, Barbara1 aMillikan, Robert1 aNock, Nora, L1 aOlshan, Andrew, F1 aPress, Michael, F1 aVaiyda, Dhananjay1 aWoods, Nancy, F1 aTaylor, Herman, A1 aZhao, Wei1 aZheng, Wei1 aEvans, Michele, K1 aHarris, Tamara, B1 aHenderson, Brian, E1 aKardia, Sharon, L R1 aKooperberg, Charles1 aLiu, Yongmei1 aMosley, Thomas, H1 aPsaty, Bruce1 aWellons, Melissa1 aWindham, Beverly, G1 aZonderman, Alan, B1 aCupples, Adrienne, L1 aDemerath, Ellen, W1 aHaiman, Christopher1 aMurabito, Joanne, M1 aRajkovic, Aleksandar uhttps://chs-nhlbi.org/node/655203475nas a2200601 4500008004100000022001400041245017800055210006900233260001300302300001000315490000600325520173700331653001002068653000902078653001002087653002002097653001902117653001102136653003202147653002202179653003402201653001302235653001902248653001102267653000902278653002202287653001602309653003602325653002702361653001602388100001802404700002202422700002302444700002002467700002402487700002302511700001202534700002402546700001702570700002202587700002102609700001702630700001702647700002102664700001902685700002302704700002202727700002302749700002102772700001902793700002502812856003602837 2014 eng d a1942-326800aSequence variation in TMEM18 in association with body mass index: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.0 aSequence variation in TMEM18 in association with body mass index c2014 Jun a344-90 v73 aBACKGROUND: Genome-wide association studies for body mass index (BMI) previously identified a locus near TMEM18. We conducted targeted sequencing of this region to investigate the role of common, low-frequency, and rare variants influencing BMI.
METHODS AND RESULTS: We sequenced TMEM18 and regions downstream of TMEM18 on chromosome 2 in 3976 individuals of European ancestry from 3 community-based cohorts (Atherosclerosis Risk in Communities, Cardiovascular Health Study, and Framingham Heart Study), including 200 adults selected for high BMI. We examined the association between BMI and variants identified in the region from nucleotide position 586 432 to 677 539 (hg18). Rare variants (minor allele frequency, <1%) were analyzed using a burden test and the sequence kernel association test. Results from the 3 cohort studies were meta-analyzed. We estimate that mean BMI is 0.43 kg/m(2) higher for each copy of the G allele of single-nucleotide polymorphism rs7596758 (minor allele frequency, 29%; P=3.46×10(-4)) using a Bonferroni threshold of P<4.6×10(-4). Analyses conditional on previous genome-wide association study single-nucleotide polymorphisms associated with BMI in the region led to attenuation of this signal and uncovered another independent (r(2)<0.2), statistically significant association, rs186019316 (P=2.11×10(-4)). Both rs186019316 and rs7596758 or proxies are located in transcription factor binding regions. No significant association with rare variants was found in either the exons of TMEM18 or the 3' genome-wide association study region.
CONCLUSIONS: Targeted sequencing around TMEM18 identified 2 novel BMI variants with possible regulatory function.
10aAdult10aAged10aAging10aBody Mass Index10aCohort Studies10aFemale10aGenetic Association Studies10aGenetic Variation10aGenome-Wide Association Study10aGenomics10aHeart Diseases10aHumans10aMale10aMembrane Proteins10aMiddle Aged10aPolymorphism, Single Nucleotide10aSequence Analysis, DNA10aYoung Adult1 aLiu, Ching-Ti1 aYoung, Kristin, L1 aBrody, Jennifer, A1 aOlden, Matthias1 aWojczynski, Mary, K1 aHeard-Costa, Nancy1 aLi, Guo1 aMorrison, Alanna, C1 aMuzny, Donna1 aGibbs, Richard, A1 aReid, Jeffrey, G1 aShao, Yaming1 aZhou, Yanhua1 aBoerwinkle, Eric1 aHeiss, Gerardo1 aWagenknecht, Lynne1 aMcKnight, Barbara1 aBorecki, Ingrid, B1 aFox, Caroline, S1 aNorth, Kari, E1 aCupples, Adrienne, L uhttps://chs-nhlbi.org/node/657903673nas a2200529 4500008004100000022001400041245019500055210006900250260001300319300001100332490000600343520199700349653000902346653002202355653001002377653002002387653004302407653001902450653004002469653001102509653002202520653003402542653001302576653001102589653000902600653001602609653003602625653002702661653005202688100001902740700002202759700002302781700002002804700002002824700001702844700002202861700001902883700001802902700001902920700002102939700002002960700001902980700002502999700003003024710005303054856003603107 2014 eng d a1942-326800aSequencing of 2 subclinical atherosclerosis candidate regions in 3669 individuals: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.0 aSequencing of 2 subclinical atherosclerosis candidate regions in c2014 Jun a359-640 v73 aBACKGROUND: Atherosclerosis, the precursor to coronary heart disease and stroke, is characterized by an accumulation of fatty cells in the arterial intimal-medial layers. Common carotid intima media thickness (cIMT) and plaque are subclinical atherosclerosis measures that predict cardiovascular disease events. Previously, genome-wide association studies demonstrated evidence for association with cIMT (SLC17A4) and plaque (PIK3CG).
METHODS AND RESULTS: We sequenced 120 kb around SLC17A4 (6p22.2) and 251 kb around PIK3CG (7q22.3) among 3669 European ancestry participants from the Atherosclerosis Risk in Communities (ARIC) study, Cardiovascular Health Study (CHS), and Framingham Heart Study (FHS) in Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Primary analyses focused on 438 common variants (minor allele frequency ≥1%), which were independently meta-analyzed. A 3' untranslated region CCDC71L variant (rs2286149), upstream from PIK3CG, was the most significant finding in cIMT (P=0.00033) and plaque (P=0.0004) analyses. A SLC17A4 intronic variant was also associated with cIMT (P=0.008). Both were in low linkage disequilibrium with the genome-wide association study single nucleotide polymorphisms. Gene-based tests including T1 count and sequence kernel association test for rare variants (minor allele frequency <1%) did not yield statistically significant associations. However, we observed nominal associations for rare variants in CCDC71L and SLC17A3 with cIMT and of the entire 7q22 region with plaque (P=0.05).
CONCLUSIONS: Common and rare variants in PIK3CG and SLC17A4 regions demonstrated modest association with subclinical atherosclerosis traits. Although not conclusive, these findings may help to understand the genetic architecture of regions previously implicated by genome-wide association studies and identify variants within these regions for further investigation in larger samples.
10aAged10aAged, 80 and over10aAging10aAtherosclerosis10aClass Ib Phosphatidylinositol 3-Kinase10aCohort Studies10aEuropean Continental Ancestry Group10aFemale10aGenetic Variation10aGenome-Wide Association Study10aGenomics10aHumans10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aSequence Analysis, DNA10aSodium-Phosphate Cotransporter Proteins, Type I1 aBis, Joshua, C1 aWhite, Charles, C1 aFranceschini, Nora1 aBrody, Jennifer1 aZhang, Xiaoling1 aMuzny, Donna1 aSantibanez, Jireh1 aGibbs, Richard1 aLiu, Xiaoming1 aLin, Honghuang1 aBoerwinkle, Eric1 aPsaty, Bruce, M1 aNorth, Kari, E1 aCupples, Adrienne, L1 aO'Donnell, Christopher, J1 aCHARGE Subclinical Atherosclerosis Working Group uhttps://chs-nhlbi.org/node/654704324nas a2200793 4500008004100000022001400041245017800055210006900233260001300302300001100315490000600326520200100332653001002333653000902343653002202352653001002374653001902384653001102403653002202414653003402436653001302470653002802483653001902511653001102530653000902541653001602550653004002566653003602606653002702642100002202669700002302691700001902714700001902733700001902752700001702771700001802788700002402806700001602830700002002846700001902866700001902885700002302904700001902927700002402946700002502970700002202995700002403017700001903041700002903060700003003089700002403119700002403143700002003167700002203187700002203209700002203231700002203253700002103275700002003296700002103316700002103337700002103358700002003379700002203399710002203421710004103443710001003484856003603494 2014 eng d a1942-326800aSequencing of SCN5A identifies rare and common variants associated with cardiac conduction: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.0 aSequencing of SCN5A identifies rare and common variants associat c2014 Jun a365-730 v73 aBACKGROUND: The cardiac sodium channel SCN5A regulates atrioventricular and ventricular conduction. Genetic variants in this gene are associated with PR and QRS intervals. We sought to characterize further the contribution of rare and common coding variation in SCN5A to cardiac conduction.
METHODS AND RESULTS: In Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study, we performed targeted exonic sequencing of SCN5A (n=3699, European ancestry individuals) and identified 4 common (minor allele frequency >1%) and 157 rare variants. Common and rare SCN5A coding variants were examined for association with PR and QRS intervals through meta-analysis of European ancestry participants from CHARGE, National Heart, Lung, and Blood Institute's Exome Sequencing Project (n=607), and the UK10K (n=1275) and by examining Exome Sequencing Project African ancestry participants (n=972). Rare coding SCN5A variants in aggregate were associated with PR interval in European and African ancestry participants (P=1.3×10(-3)). Three common variants were associated with PR and QRS interval duration among European ancestry participants and one among African ancestry participants. These included 2 well-known missense variants: rs1805124 (H558R) was associated with PR and QRS shortening in European ancestry participants (P=6.25×10(-4) and P=5.2×10(-3), respectively) and rs7626962 (S1102Y) was associated with PR shortening in those of African ancestry (P=2.82×10(-3)). Among European ancestry participants, 2 novel synonymous variants, rs1805126 and rs6599230, were associated with cardiac conduction. Our top signal, rs1805126 was associated with PR and QRS lengthening (P=3.35×10(-7) and P=2.69×10(-4), respectively) and rs6599230 was associated with PR shortening (P=2.67×10(-5)).
CONCLUSIONS: By sequencing SCN5A, we identified novel common and rare coding variants associated with cardiac conduction.
10aAdult10aAged10aAged, 80 and over10aAging10aCohort Studies10aFemale10aGenetic Variation10aGenome-Wide Association Study10aGenomics10aHeart Conduction System10aHeart Diseases10aHumans10aMale10aMiddle Aged10aNAV1.5 Voltage-Gated Sodium Channel10aPolymorphism, Single Nucleotide10aSequence Analysis, DNA1 aMagnani, Jared, W1 aBrody, Jennifer, A1 aPrins, Bram, P1 aArking, Dan, E1 aLin, Honghuang1 aYin, Xiaoyan1 aLiu, Ching-Ti1 aMorrison, Alanna, C1 aZhang, Feng1 aSpector, Tim, D1 aAlonso, Alvaro1 aBis, Joshua, C1 aHeckbert, Susan, R1 aLumley, Thomas1 aSitlani, Colleen, M1 aCupples, Adrienne, L1 aLubitz, Steven, A1 aSoliman, Elsayed, Z1 aPulit, Sara, L1 aNewton-Cheh, Christopher1 aO'Donnell, Christopher, J1 aEllinor, Patrick, T1 aBenjamin, Emelia, J1 aMuzny, Donna, M1 aGibbs, Richard, A1 aSantibanez, Jireh1 aTaylor, Herman, A1 aRotter, Jerome, I1 aLange, Leslie, A1 aPsaty, Bruce, M1 aJackson, Rebecca1 aRich, Stephen, S1 aBoerwinkle, Eric1 aJamshidi, Yalda1 aSotoodehnia, Nona1 aCHARGE Consortium1 aNHLBI Exome Sequencing Project (ESP)1 aUK10K uhttps://chs-nhlbi.org/node/658303990nas a2200757 4500008004100000022001400041245017100055210006900226260001300295300001100308490000600319520184400325653001002169653000902179653002202188653001002210653001902220653001102239653002202250653003402272653001302306653001902319653001102338653000902349653001602358653003602374653002002410653002702430100001902457700001402476700002302490700001902513700001902532700001902551700002202570700002102592700002402613700002102637700001802658700001802676700002002694700002302714700003002737700002302767700001602790700001702806700001902823700001402842700001602856700002402872700001902896700002402915700001802939700002202957700001902979700001702998700002403015700002403039700002303063700002003086700002003106700002503126700002403151700002103175856003603196 2014 eng d a1942-326800aStrategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.0 aStrategies to design and analyze targeted sequencing data cohort c2014 Jun a335-430 v73 aBACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.
METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with ≥1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency ≥1%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.
CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.
10aAdult10aAged10aAged, 80 and over10aAging10aCohort Studies10aFemale10aGenetic Variation10aGenome-Wide Association Study10aGenomics10aHeart Diseases10aHumans10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aResearch Design10aSequence Analysis, DNA1 aLin, Honghuang1 aWang, Min1 aBrody, Jennifer, A1 aBis, Joshua, C1 aDupuis, Josée1 aLumley, Thomas1 aMcKnight, Barbara1 aRice, Kenneth, M1 aSitlani, Colleen, M1 aReid, Jeffrey, G1 aBressler, Jan1 aLiu, Xiaoming1 aDavis, Brian, C1 aJohnson, Andrew, D1 aO'Donnell, Christopher, J1 aKovar, Christie, L1 aDinh, Huyen1 aWu, Yuanqing1 aNewsham, Irene1 aChen, Han1 aBroka, Andi1 aDeStefano, Anita, L1 aGupta, Mayetri1 aLunetta, Kathryn, L1 aLiu, Ching-Ti1 aWhite, Charles, C1 aXing, Chuanhua1 aZhou, Yanhua1 aBenjamin, Emelia, J1 aSchnabel, Renate, B1 aHeckbert, Susan, R1 aPsaty, Bruce, M1 aMuzny, Donna, M1 aCupples, Adrienne, L1 aMorrison, Alanna, C1 aBoerwinkle, Eric uhttps://chs-nhlbi.org/node/657804315nas a2200901 4500008004100000022001400041245006300055210006000118260001600178300001200194490000700206520174600213653002201959653003701981653001802018653004002036653001802076653003402094653001302128653001102141653002002152653001502172653002702187653001402214653003602228653002802264100002302292700002502315700002002340700002602360700002302386700002002409700002102429700002202450700002002472700002002492700002302512700002202535700001902557700002002576700002502596700001802621700001902639700002102658700002102679700002402700700002102724700001602745700001402761700002102775700002302796700002002819700002202839700002102861700001902882700001502901700001902916700002102935700001902956700002802975700002303003700002103026700001803047700002503065700002003090700002303110700002503133700002203158700003003180700002303210700002103233700002203254700001903276710002203295710001103317710004903328856003603377 2014 eng d a1460-208300aTrans-ethnic meta-analysis of white blood cell phenotypes.0 aTransethnic metaanalysis of white blood cell phenotypes c2014 Dec 20 a6944-600 v233 aWhite blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.
10aAfrican Americans10aAsian Continental Ancestry Group10aBayes Theorem10aEuropean Continental Ancestry Group10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHumans10aLeukocyte Count10aLeukocytes10aLinkage Disequilibrium10aPhenotype10aPolymorphism, Single Nucleotide10aQuantitative Trait Loci1 aKeller, Margaux, F1 aReiner, Alexander, P1 aOkada, Yukinori1 avan Rooij, Frank, J A1 aJohnson, Andrew, D1 aChen, Ming-Huei1 aSmith, Albert, V1 aMorris, Andrew, P1 aTanaka, Toshiko1 aFerrucci, Luigi1 aZonderman, Alan, B1 aLettre, Guillaume1 aHarris, Tamara1 aGarcia, Melissa1 aBandinelli, Stefania1 aQayyum, Rehan1 aYanek, Lisa, R1 aBecker, Diane, M1 aBecker, Lewis, C1 aKooperberg, Charles1 aKeating, Brendan1 aReis, Jared1 aTang, Hua1 aBoerwinkle, Eric1 aKamatani, Yoichiro1 aMatsuda, Koichi1 aKamatani, Naoyuki1 aNakamura, Yusuke1 aKubo, Michiaki1 aLiu, Simin1 aDehghan, Abbas1 aFelix, Janine, F1 aHofman, Albert1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aFranco, Oscar, H1 aLongo, Dan, L1 aSingleton, Andrew, B1 aPsaty, Bruce, M1 aEvans, Michelle, K1 aCupples, Adrienne, L1 aRotter, Jerome, I1 aO'Donnell, Christopher, J1 aTakahashi, Atsushi1 aWilson, James, G1 aGanesh, Santhi, K1 aNalls, Mike, A1 aCHARGE Hematology1 aCOGENT1 aBioBank Japan Project (RIKEN) Working Groups uhttps://chs-nhlbi.org/node/657305955nas a2201657 4500008004100000022001400041245011000055210006900165260001600234300001100250490000700261520138800268653001001656653000901666653002201675653002101697653001901718653001801737653001001755653001101765653002201776653001901798653001701817653003401834653001301868653001101881653001101892653000901903653001601912653001401928653003601942653002801978653002702006653001902033653002702052653002602079100002102105700001402126700001402140700001602154700002202170700002202192700001702214700002002231700002102251700002102272700001302293700002002306700001702326700001502343700001702358700002002375700001402395700002702409700001802436700002202454700001602476700001902492700001702511700002102528700002302549700002002572700001802592700002202610700001802632700001502650700001202665700001702677700001502694700001802709700001902727700001902746700001902765700002502784700002602809700002102835700002502856700002102881700001902902700002502921700001702946700002502963700001202988700002303000700002003023700002603043700002903069700002303098700002803121700001803149700002003167700002303187700002103210700001903231700001803250700002803268700001903296700002403315700002303339700002803362700001703390700002203407700002203429700002403451700002403475700002003499700002303519700002203542700001603564700001703580700002403597700002003621700001803641700002003659700002103679700001603700700001903716700002203735700002803757700002303785700003003808700001903838700001903857700002503876700002103901700002003922700002103942700002203963700001603985700002004001700002504021700002404046700002104070700002604091700002504117700002104142700002204163700002304185710005304208856003604261 2014 eng d a1537-660500aWhole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.0 aWholeexome sequencing identifies rare and lowfrequency coding va c2014 Feb 06 a233-450 v943 aElevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.
10aAdult10aAged10aApolipoproteins E10aCholesterol, LDL10aCohort Studies10aDyslipidemias10aExome10aFemale10aFollow-Up Studies10aGene Frequency10aGenetic Code10aGenome-Wide Association Study10aGenotype10aHumans10aLipase10aMale10aMiddle Aged10aPhenotype10aPolymorphism, Single Nucleotide10aProprotein Convertase 910aProprotein Convertases10aReceptors, LDL10aSequence Analysis, DNA10aSerine Endopeptidases1 aLange, Leslie, A1 aHu, Youna1 aZhang, He1 aXue, Chenyi1 aSchmidt, Ellen, M1 aTang, Zheng-Zheng1 aBizon, Chris1 aLange, Ethan, M1 aSmith, Joshua, D1 aTurner, Emily, H1 aJun, Goo1 aKang, Hyun, Min1 aPeloso, Gina1 aAuer, Paul1 aLi, Kuo-Ping1 aFlannick, Jason1 aZhang, Ji1 aFuchsberger, Christian1 aGaulton, Kyle1 aLindgren, Cecilia1 aLocke, Adam1 aManning, Alisa1 aSim, Xueling1 aRivas, Manuel, A1 aHolmen, Oddgeir, L1 aGottesman, Omri1 aLu, Yingchang1 aRuderfer, Douglas1 aStahl, Eli, A1 aDuan, Qing1 aLi, Yun1 aDurda, Peter1 aJiao, Shuo1 aIsaacs, Aaron1 aHofman, Albert1 aBis, Joshua, C1 aCorrea, Adolfo1 aGriswold, Michael, E1 aJakobsdottir, Johanna1 aSmith, Albert, V1 aSchreiner, Pamela, J1 aFeitosa, Mary, F1 aZhang, Qunyuan1 aHuffman, Jennifer, E1 aCrosby, Jacy1 aWassel, Christina, L1 aDo, Ron1 aFranceschini, Nora1 aMartin, Lisa, W1 aRobinson, Jennifer, G1 aAssimes, Themistocles, L1 aCrosslin, David, R1 aRosenthal, Elisabeth, A1 aTsai, Michael1 aRieder, Mark, J1 aFarlow, Deborah, N1 aFolsom, Aaron, R1 aLumley, Thomas1 aFox, Ervin, R1 aCarlson, Christopher, S1 aPeters, Ulrike1 aJackson, Rebecca, D1 aDuijn, Cornelia, M1 aUitterlinden, André, G1 aLevy, Daniel1 aRotter, Jerome, I1 aTaylor, Herman, A1 aGudnason, Vilmundur1 aSiscovick, David, S1 aFornage, Myriam1 aBorecki, Ingrid, B1 aHayward, Caroline1 aRudan, Igor1 aChen, Eugene1 aBottinger, Erwin, P1 aLoos, Ruth, J F1 aSætrom, Pål1 aHveem, Kristian1 aBoehnke, Michael1 aGroop, Leif1 aMcCarthy, Mark1 aMeitinger, Thomas1 aBallantyne, Christie, M1 aGabriel, Stacey, B1 aO'Donnell, Christopher, J1 aPost, Wendy, S1 aNorth, Kari, E1 aReiner, Alexander, P1 aBoerwinkle, Eric1 aPsaty, Bruce, M1 aAltshuler, David1 aKathiresan, Sekar1 aLin, Dan-Yu1 aJarvik, Gail, P1 aCupples, Adrienne, L1 aKooperberg, Charles1 aWilson, James, G1 aNickerson, Deborah, A1 aAbecasis, Goncalo, R1 aRich, Stephen, S1 aTracy, Russell, P1 aWiller, Cristen, J1 aNHLBI Grand Opportunity Exome Sequencing Project uhttps://chs-nhlbi.org/node/657705848nas a2201069 4500008004100000022001400041245018600055210006900241260001300310300001200323490000800335520268400343653001803027653001903045653003203064653003803096653003403134653001103168653001803179653002003197653001203217653002303229653002803252653000903280653001803289653001603307653003603323653001703359100002203376700002003398700002703418700002403445700002003469700002403489700003203513700002003545700002803565700002303593700001603616700002003632700002903652700001903681700003203700700002503732700001803757700002003775700001903795700002303814700002103837700002203858700002003880700002303900700002403923700002103947700002103968700002603989700002104015700002004036700002104056700001804077700002504095700001704120700002004137700002304157700002404180700002204204700001904226700001604245700002004261700002104281700002404302700002104326700001704347700002104364700002804385700002004413700002104433700002004454700002504474700002304499700002004522700002104542700001904563700002304582700002504605700002104630700002204651700002504673700002004698700002404718856003604742 2015 eng d a1938-320700aConsumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians.0 aConsumption of meat is associated with higher fasting glucose an c2015 Nov a1266-780 v1023 aBACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.
OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.
DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.
RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.
CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
10aBlood Glucose10aCohort Studies10aGenetic Association Studies10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aHyperglycemia10aHyperinsulinism10aInsulin10aInsulin Resistance10aInsulin-Secreting Cells10aMeat10aMeat Products10aMiddle Aged10aPolymorphism, Single Nucleotide10aRisk Factors1 aFretts, Amanda, M1 aFollis, Jack, L1 aNettleton, Jennifer, A1 aLemaitre, Rozenn, N1 aNgwa, Julius, S1 aWojczynski, Mary, K1 aKalafati, Ioanna, Panagiota1 aVarga, Tibor, V1 aFrazier-Wood, Alexis, C1 aHouston, Denise, K1 aLahti, Jari1 aEricson, Ulrika1 avan den Hooven, Edith, H1 aMikkilä, Vera1 ade Jong, Jessica, C Kiefte-1 aMozaffarian, Dariush1 aRice, Kenneth1 aRenstrom, Frida1 aNorth, Kari, E1 aMcKeown, Nicola, M1 aFeitosa, Mary, F1 aKanoni, Stavroula1 aSmith, Caren, E1 aGarcia, Melissa, E1 aTiainen, Anna-Maija1 aSonestedt, Emily1 aManichaikul, Ani1 avan Rooij, Frank, J A1 aDimitriou, Maria1 aRaitakari, Olli1 aPankow, James, S1 aDjoussé, Luc1 aProvince, Michael, A1 aHu, Frank, B1 aLai, Chao-Qiang1 aKeller, Margaux, F1 aPerälä, Mia-Maria1 aRotter, Jerome, I1 aHofman, Albert1 aGraff, Misa1 aKähönen, Mika1 aMukamal, Kenneth1 aJohansson, Ingegerd1 aOrdovas, Jose, M1 aLiu, Yongmei1 aMännistö, Satu1 aUitterlinden, André, G1 aDeloukas, Panos1 aSeppälä, Ilkka1 aPsaty, Bruce, M1 aCupples, Adrienne, L1 aBorecki, Ingrid, B1 aFranks, Paul, W1 aArnett, Donna, K1 aNalls, Mike, A1 aEriksson, Johan, G1 aOrho-Melander, Marju1 aFranco, Oscar, H1 aLehtimäki, Terho1 aDedoussis, George, V1 aMeigs, James, B1 aSiscovick, David, S uhttps://chs-nhlbi.org/node/684405255nas a2200949 4500008004100000022001400041245015700055210006900212260000900281300001300290490000700303520251800310653002202828653000902850653002802859653002802887653004002915653001102955653003402966653001103000653001703011653001403028653000903042653001603051653003603067653002203103100001903125700002103144700001603165700002203181700002603203700001603229700002103245700002303266700001603289700002003305700002203325700002203347700002103369700002303390700002303413700002003436700002203456700002303478700002103501700002203522700002003544700002103564700002203585700001803607700002003625700002503645700002203670700002303692700001703715700002103732700002303753700002403776700002003800700002103820700002203841700002503863700002803888700002203916700001403938700001903952700001903971700002003990700002604010700002404036700002704060700001904087700002404106700002204130700001604152700001904168700002304187700002104210700002004231700001804251856003604269 2015 eng d a1932-620300aDrug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium.0 aDrugGene Interactions of Antihypertensive Medications and Risk o c2015 ae01404960 v103 aBACKGROUND: Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.
METHODS: Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).
RESULTS: Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD.
10aAfrican Americans10aAged10aAntihypertensive Agents10aCardiovascular Diseases10aEuropean Continental Ancestry Group10aFemale10aGenome-Wide Association Study10aHumans10aHypertension10aIncidence10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aTreatment Outcome1 aBis, Joshua, C1 aSitlani, Colleen1 aIrvin, Ryan1 aAvery, Christy, L1 aSmith, Albert, Vernon1 aSun, Fangui1 aEvans, Daniel, S1 aMusani, Solomon, K1 aLi, Xiaohui1 aTrompet, Stella1 aKrijthe, Bouwe, P1 aHarris, Tamara, B1 aQuibrera, Miguel1 aBrody, Jennifer, A1 aDemissie, Serkalem1 aDavis, Barry, R1 aWiggins, Kerri, L1 aTranah, Gregory, J1 aLange, Leslie, A1 aSotoodehnia, Nona1 aStott, David, J1 aFranco, Oscar, H1 aLauner, Lenore, J1 aStürmer, Til1 aTaylor, Kent, D1 aCupples, Adrienne, L1 aEckfeldt, John, H1 aSmith, Nicholas, L1 aLiu, Yongmei1 aWilson, James, G1 aHeckbert, Susan, R1 aBuckley, Brendan, M1 aIkram, Arfan, M1 aBoerwinkle, Eric1 aChen, Yii-Der Ida1 ade Craen, Anton, J M1 aUitterlinden, André, G1 aRotter, Jerome, I1 aFord, Ian1 aHofman, Albert1 aSattar, Naveed1 aSlagboom, Eline1 aWestendorp, Rudi, G J1 aGudnason, Vilmundur1 aVasan, Ramachandran, S1 aLumley, Thomas1 aCummings, Steven, R1 aTaylor, Herman, A1 aPost, Wendy1 aJukema, Wouter1 aStricker, Bruno, H1 aWhitsel, Eric, A1 aPsaty, Bruce, M1 aArnett, Donna uhttps://chs-nhlbi.org/node/687506191nas a2201513 4500008004100000022001400041245010300055210006900158260001500227300001000242490000800252520194100260653001602201653001702217653001202234653002202246653002502268653002102293653002802314653001002342653001102352653003802363653002502401653001702426653001102443653000902454653001602463653001302479653002602492653005302518653001902571653001802590653001802608100001202626700002402638700001802662700002902680700001802709700002802727700001702755700002002772700001502792700001202807700002002819700002102839700002102860700002002881700001802901700002202919700002302941700002302964700002202987700002003009700002803029700002103057700001703078700002403095700002803119700001803147700002303165700002203188700002403210700002203234700001903256700002203275700001903297700001803316700002903334700001503363700002203378700002003400700002003420700002203440700001503462700002303477700001603500700001903516700001703535700001703552700002903569700001903598700002003617700002103637700002203658700002303680700002003703700001903723700002203742700001203764700002103776700002003797700002403817700002003841700002503861700002103886700002103907700002403928700002203952700002503974700002103999700002404020700002104044700001904065700002004084700002204104700002204126700002004148700002004168700002804188700002404216700002404240700002104264700002004285700002504305700002404330700002004354700002604374700002504400700001804425700002604443700002104469700002304490700003004513700002104543700002004564700002204584710003504606856003604641 2015 eng d a1476-468700aExome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction.0 aExome sequencing identifies rare LDLR and APOA5 alleles conferri c2015 Feb 5 a102-60 v5183 aMyocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.
10aAge Factors10aAge of Onset10aAlleles10aApolipoproteins A10aCase-Control Studies10aCholesterol, LDL10aCoronary Artery Disease10aExome10aFemale10aGenetic Predisposition to Disease10aGenetics, Population10aHeterozygote10aHumans10aMale10aMiddle Aged10aMutation10aMyocardial Infarction10aNational Heart, Lung, and Blood Institute (U.S.)10aReceptors, LDL10aTriglycerides10aUnited States1 aDo, Ron1 aStitziel, Nathan, O1 aWon, Hong-Hee1 aJørgensen, Anders, Berg1 aDuga, Stefano1 aMerlini, Pier, Angelica1 aKiezun, Adam1 aFarrall, Martin1 aGoel, Anuj1 aZuk, Or1 aGuella, Illaria1 aAsselta, Rosanna1 aLange, Leslie, A1 aPeloso, Gina, M1 aAuer, Paul, L1 aGirelli, Domenico1 aMartinelli, Nicola1 aFarlow, Deborah, N1 aDePristo, Mark, A1 aRoberts, Robert1 aStewart, Alexander, F R1 aSaleheen, Danish1 aDanesh, John1 aEpstein, Stephen, E1 aSivapalaratnam, Suthesh1 aHovingh, Kees1 aKastelein, John, J1 aSamani, Nilesh, J1 aSchunkert, Heribert1 aErdmann, Jeanette1 aShah, Svati, H1 aKraus, William, E1 aDavies, Robert1 aNikpay, Majid1 aJohansen, Christopher, T1 aWang, Jian1 aHegele, Robert, A1 aHechter, Eliana1 aMärz, Winfried1 aKleber, Marcus, E1 aHuang, Jie1 aJohnson, Andrew, D1 aLi, Mingyao1 aBurke, Greg, L1 aGross, Myron1 aLiu, Yongmei1 aAssimes, Themistocles, L1 aHeiss, Gerardo1 aLange, Ethan, M1 aFolsom, Aaron, R1 aTaylor, Herman, A1 aOlivieri, Oliviero1 aHamsten, Anders1 aClarke, Robert1 aReilly, Dermot, F1 aYin, Wu1 aRivas, Manuel, A1 aDonnelly, Peter1 aRossouw, Jacques, E1 aPsaty, Bruce, M1 aHerrington, David, M1 aWilson, James, G1 aRich, Stephen, S1 aBamshad, Michael, J1 aTracy, Russell, P1 aCupples, Adrienne, L1 aRader, Daniel, J1 aReilly, Muredach, P1 aSpertus, John, A1 aCresci, Sharon1 aHartiala, Jaana1 aTang, W, H Wilson1 aHazen, Stanley, L1 aAllayee, Hooman1 aReiner, Alex, P1 aCarlson, Christopher, S1 aKooperberg, Charles1 aJackson, Rebecca, D1 aBoerwinkle, Eric1 aLander, Eric, S1 aSchwartz, Stephen, M1 aSiscovick, David, S1 aMcPherson, Ruth1 aTybjaerg-Hansen, Anne1 aAbecasis, Goncalo, R1 aWatkins, Hugh1 aNickerson, Deborah, A1 aArdissino, Diego1 aSunyaev, Shamil, R1 aO'Donnell, Christopher, J1 aAltshuler, David1 aGabriel, Stacey1 aKathiresan, Sekar1 aNHLBI Exome Sequencing Project uhttps://chs-nhlbi.org/node/669104825nas a2201141 4500008004100000022001400041245010700055210007000162260001600232300001200248490000700260520164000267653001001907653002001917653002501937653001801962653002301980653004002003653001102043653001702054653003402071653001102105653000902116653001202125653003602137100002702173700002002200700002002220700002002240700001902260700002002279700002402299700002002323700002402343700002302367700002402390700002302414700002402437700001402461700002102475700002102496700002202517700001802539700001902557700001902576700002402595700001902619700002302638700002402661700002002685700001702705700001602722700001702738700002502755700001502780700001802795700001902813700002002832700001402852700002002866700002102886700002102907700002102928700001602949700002002965700002102985700002603006700002003032700001703052700002003069700001803089700001903107700001903126700001903145700002303164700001903187700002803206700002403234700002103258700002503279700002003304700002303324700001603347700002803363700002303391700002503414700001103439700002003450700002503470700002503495700002003520700002203540700002003562700002503582700002003607700002003627856003603647 2015 eng d a1460-208300aGene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry.0 aGene × dietary pattern interactions in obesity analysis of up to c2015 Aug 15 a4728-380 v243 aObesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.
10aAdult10aBody Mass Index10aCase-Control Studies10aDiet, Western10aEpistasis, Genetic10aEuropean Continental Ancestry Group10aFemale10aGenetic Loci10aGenome-Wide Association Study10aHumans10aMale10aObesity10aPolymorphism, Single Nucleotide1 aNettleton, Jennifer, A1 aFollis, Jack, L1 aNgwa, Julius, S1 aSmith, Caren, E1 aAhmad, Shafqat1 aTanaka, Toshiko1 aWojczynski, Mary, K1 aVoortman, Trudy1 aLemaitre, Rozenn, N1 aKristiansson, Kati1 aNuotio, Marja-Liisa1 aHouston, Denise, K1 aPerälä, Mia-Maria1 aQi, Qibin1 aSonestedt, Emily1 aManichaikul, Ani1 aKanoni, Stavroula1 aGanna, Andrea1 aMikkilä, Vera1 aNorth, Kari, E1 aSiscovick, David, S1 aHarald, Kennet1 aMcKeown, Nicola, M1 aJohansson, Ingegerd1 aRissanen, Harri1 aLiu, Yongmei1 aLahti, Jari1 aHu, Frank, B1 aBandinelli, Stefania1 aRukh, Gull1 aRich, Stephen1 aBooij, Lisanne1 aDmitriou, Maria1 aAx, Erika1 aRaitakari, Olli1 aMukamal, Kenneth1 aMännistö, Satu1 aHallmans, Göran1 aJula, Antti1 aEricson, Ulrika1 aJacobs, David, R1 avan Rooij, Frank, J A1 aDeloukas, Panos1 aSjogren, Per1 aKähönen, Mika1 aDjoussé, Luc1 aPerola, Markus1 aBarroso, Inês1 aHofman, Albert1 aStirrups, Kathleen1 aViikari, Jorma1 aUitterlinden, André, G1 aKalafati, Ioanna, P1 aFranco, Oscar, H1 aMozaffarian, Dariush1 aSalomaa, Veikko1 aBorecki, Ingrid, B1 aKnekt, Paul1 aKritchevsky, Stephen, B1 aEriksson, Johan, G1 aDedoussis, George, V1 aQi, Lu1 aFerrucci, Luigi1 aOrho-Melander, Marju1 aZillikens, Carola, M1 aIngelsson, Erik1 aLehtimäki, Terho1 aRenstrom, Frida1 aCupples, Adrienne, L1 aLoos, Ruth, J F1 aFranks, Paul, W uhttps://chs-nhlbi.org/node/680202719nas a2200469 4500008004100000022001400041245010800055210006900163260001600232300001100248490000700259520132600266653000901592653001001601653002801611653001901639653002401658653002801682653003401710653003301744653002201777653001801799653003401817653001101851653002501862653002701887653002001914653002101934653002001955653001801975100002401993700002102017700001902038700002202057700002502079700002202104700002102126700002502147700002102172700002002193856003602213 2015 eng d a1097-025800aGeneralized estimating equations for genome-wide association studies using longitudinal phenotype data.0 aGeneralized estimating equations for genomewide association stud c2015 Jan 15 a118-300 v343 aMany longitudinal cohort studies have both genome-wide measures of genetic variation and repeated measures of phenotypes and environmental exposures. Genome-wide association study analyses have typically used only cross-sectional data to evaluate quantitative phenotypes and binary traits. Incorporation of repeated measures may increase power to detect associations, but also requires specialized analysis methods. Here, we discuss one such method-generalized estimating equations (GEE)-in the contexts of analysis of main effects of rare genetic variants and analysis of gene-environment interactions. We illustrate the potential for increased power using GEE analyses instead of cross-sectional analyses. We also address challenges that arise, such as the need for small-sample corrections when the minor allele frequency of a genetic variant and/or the prevalence of an environmental exposure is low. To illustrate methods for detection of gene-drug interactions on a genome-wide scale, using repeated measures data, we conduct single-study analyses and meta-analyses across studies in three large cohort studies participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium-the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Rotterdam Study.
10aAged10aAging10aCardiovascular Diseases10aCohort Studies10aComputer Simulation10aCross-Sectional Studies10aEpidemiologic Research Design10aGene-Environment Interaction10aGenetic Variation10aGenome, Human10aGenome-Wide Association Study10aHumans10aLongitudinal Studies10aMeta-Analysis as Topic10aModels, Genetic10aPharmacogenetics10aRisk Assessment10aUnited States1 aSitlani, Colleen, M1 aRice, Kenneth, M1 aLumley, Thomas1 aMcKnight, Barbara1 aCupples, Adrienne, L1 aAvery, Christy, L1 aNoordam, Raymond1 aStricker, Bruno, H C1 aWhitsel, Eric, A1 aPsaty, Bruce, M uhttps://chs-nhlbi.org/node/660209013nas a2202797 4500008004100000022001400041245011400055210006900169260000900238300000900247490000600256520115900262653003901421653001801460653003001478653004001508653001001548653001201558653003201570653001701602653003801619653002201657653003701679653002601716653001101742653001201753653001801765653004401783653003601827100002101863700001901884700002101903700001601924700002301940700002301963700001801986700002502004700002402029700002202053700002002075700001502095700002502110700001302135700001802148700003102166700001802197700002102215700001102236700002602247700002502273700002002298700001902318700001702337700002302354700002002377700002302397700002302420700001702443700001602460700001802476700002602494700002102520700002002541700001202561700002002573700002102593700002402614700001902638700002502657700002502682700002302707700002102730700002102751700002202772700002302794700002502817700002002842700002002862700002302882700001602905700002402921700001402945700002302959700002502982700002103007700002303028700002203051700001903073700001703092700001903109700002003128700001903148700002203167700001903189700002003208700002403228700002203252700002503274700002303299700002203322700002303344700002403367700001503391700002003406700002003426700002303446700001403469700002103483700001703504700001803521700002303539700002303562700002503585700002303610700002403633700001903657700002403676700001903700700002203719700002003741700001403761700001803775700001703793700001703810700001603827700001703843700002503860700002103885700002203906700002203928700002003950700002203970700002003992700002704012700001704039700002304056700002104079700002004100700001904120700002604139700001804165700001904183700002104202700002004223700001404243700002004257700002004277700002704297700002304324700002004347700002804367700001804395700002304413700002304436700002704459700001704486700002104503700002704524700001804551700001904569700001904588700002104607700001904628700002004647700002504667700001904692700002004711700002204731700002004753700002304773700002004796700002004816700002104836700002104857700002204878700001704900700002604917700001904943700002404962700002204986700002005008700002005028700002105048700002005069700002205089700002405111700002005135700002205155700002605177700002205203700001905225700002405244700002405268700002205292700001705314700001905331700003005350700002305380700002505403700002105428700001905449700002505468700002105493700002005514700001605534700002505550700002005575700002805595700001705623700001805640700001805658700002405676700001905700700002305719700002305742700001905765700002005784700001905804700002305823700002505846700002405871700002105895700002005916700002005936700002005956700002105976700002505997700002406022700001906046700002206065700002006087700002106107700002206128710002906150856003606179 2015 eng d a2041-172300aLow-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility.0 aLowfrequency and rare exome chip variants associate with fasting c2015 a58970 v63 aFasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
10aAfrican Continental Ancestry Group10aBlood Glucose10aDiabetes Mellitus, Type 210aEuropean Continental Ancestry Group10aExome10aFasting10aGenetic Association Studies10aGenetic Loci10aGenetic Predisposition to Disease10aGenetic Variation10aGlucagon-Like Peptide-1 Receptor10aGlucose-6-Phosphatase10aHumans10aInsulin10aMutation Rate10aOligonucleotide Array Sequence Analysis10aPolymorphism, Single Nucleotide1 aWessel, Jennifer1 aChu, Audrey, Y1 aWillems, Sara, M1 aWang, Shuai1 aYaghootkar, Hanieh1 aBrody, Jennifer, A1 aDauriz, Marco1 aHivert, Marie-France1 aRaghavan, Sridharan1 aLipovich, Leonard1 aHidalgo, Bertha1 aFox, Keolu1 aHuffman, Jennifer, E1 aAn, Ping1 aLu, Yingchang1 aRasmussen-Torvik, Laura, J1 aGrarup, Niels1 aEhm, Margaret, G1 aLi, Li1 aBaldridge, Abigail, S1 aStančáková, Alena1 aAbrol, Ravinder1 aBesse, Céline1 aBoland, Anne1 aBork-Jensen, Jette1 aFornage, Myriam1 aFreitag, Daniel, F1 aGarcia, Melissa, E1 aGuo, Xiuqing1 aHara, Kazuo1 aIsaacs, Aaron1 aJakobsdottir, Johanna1 aLange, Leslie, A1 aLayton, Jill, C1 aLi, Man1 aZhao, Jing, Hua1 aMeidtner, Karina1 aMorrison, Alanna, C1 aNalls, Mike, A1 aPeters, Marjolein, J1 aSabater-Lleal, Maria1 aSchurmann, Claudia1 aSilveira, Angela1 aSmith, Albert, V1 aSoutham, Lorraine1 aStoiber, Marcus, H1 aStrawbridge, Rona, J1 aTaylor, Kent, D1 aVarga, Tibor, V1 aAllin, Kristine, H1 aAmin, Najaf1 aAponte, Jennifer, L1 aAung, Tin1 aBarbieri, Caterina1 aBihlmeyer, Nathan, A1 aBoehnke, Michael1 aBombieri, Cristina1 aBowden, Donald, W1 aBurns, Sean, M1 aChen, Yuning1 aChen, Yii-DerI1 aCheng, Ching-Yu1 aCorrea, Adolfo1 aCzajkowski, Jacek1 aDehghan, Abbas1 aEhret, Georg, B1 aEiriksdottir, Gudny1 aEscher, Stefan, A1 aFarmaki, Aliki-Eleni1 aFrånberg, Mattias1 aGambaro, Giovanni1 aGiulianini, Franco1 aGoddard, William, A1 aGoel, Anuj1 aGottesman, Omri1 aGrove, Megan, L1 aGustafsson, Stefan1 aHai, Yang1 aHallmans, Göran1 aHeo, Jiyoung1 aHoffmann, Per1 aIkram, Mohammad, K1 aJensen, Richard, A1 aJørgensen, Marit, E1 aJørgensen, Torben1 aKaraleftheri, Maria1 aKhor, Chiea, C1 aKirkpatrick, Andrea1 aKraja, Aldi, T1 aKuusisto, Johanna1 aLange, Ethan, M1 aLee, I, T1 aLee, Wen-Jane1 aLeong, Aaron1 aLiao, Jiemin1 aLiu, Chunyu1 aLiu, Yongmei1 aLindgren, Cecilia, M1 aLinneberg, Allan1 aMalerba, Giovanni1 aMamakou, Vasiliki1 aMarouli, Eirini1 aMaruthur, Nisa, M1 aMatchan, Angela1 aMcKean-Cowdin, Roberta1 aMcLeod, Olga1 aMetcalf, Ginger, A1 aMohlke, Karen, L1 aMuzny, Donna, M1 aNtalla, Ioanna1 aPalmer, Nicholette, D1 aPasko, Dorota1 aPeter, Andreas1 aRayner, Nigel, W1 aRenstrom, Frida1 aRice, Ken1 aSala, Cinzia, F1 aSennblad, Bengt1 aSerafetinidis, Ioannis1 aSmith, Jennifer, A1 aSoranzo, Nicole1 aSpeliotes, Elizabeth, K1 aStahl, Eli, A1 aStirrups, Kathleen1 aTentolouris, Nikos1 aThanopoulou, Anastasia1 aTorres, Mina1 aTraglia, Michela1 aTsafantakis, Emmanouil1 aJavad, Sundas1 aYanek, Lisa, R1 aZengini, Eleni1 aBecker, Diane, M1 aBis, Joshua, C1 aBrown, James, B1 aCupples, Adrienne, L1 aHansen, Torben1 aIngelsson, Erik1 aKarter, Andrew, J1 aLorenzo, Carlos1 aMathias, Rasika, A1 aNorris, Jill, M1 aPeloso, Gina, M1 aSheu, Wayne, H-H1 aToniolo, Daniela1 aVaidya, Dhananjay1 aVarma, Rohit1 aWagenknecht, Lynne, E1 aBoeing, Heiner1 aBottinger, Erwin, P1 aDedoussis, George1 aDeloukas, Panos1 aFerrannini, Ele1 aFranco, Oscar, H1 aFranks, Paul, W1 aGibbs, Richard, A1 aGudnason, Vilmundur1 aHamsten, Anders1 aHarris, Tamara, B1 aHattersley, Andrew, T1 aHayward, Caroline1 aHofman, Albert1 aJansson, Jan-Håkan1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLevy, Daniel1 aOostra, Ben, A1 aO'Donnell, Christopher, J1 aO'Rahilly, Stephen1 aPadmanabhan, Sandosh1 aPankow, James, S1 aPolasek, Ozren1 aProvince, Michael, A1 aRich, Stephen, S1 aRidker, Paul, M1 aRudan, Igor1 aSchulze, Matthias, B1 aSmith, Blair, H1 aUitterlinden, André, G1 aWalker, Mark1 aWatkins, Hugh1 aWong, Tien, Y1 aZeggini, Eleftheria1 aLaakso, Markku1 aBorecki, Ingrid, B1 aChasman, Daniel, I1 aPedersen, Oluf1 aPsaty, Bruce, M1 aTai, Shyong, E1 aDuijn, Cornelia, M1 aWareham, Nicholas, J1 aWaterworth, Dawn, M1 aBoerwinkle, Eric1 aKao, Linda, W H1 aFlorez, Jose, C1 aLoos, Ruth, J F1 aWilson, James, G1 aFrayling, Timothy, M1 aSiscovick, David, S1 aDupuis, Josée1 aRotter, Jerome, I1 aMeigs, James, B1 aScott, Robert, A1 aGoodarzi, Mark, O1 aEPIC-InterAct Consortium uhttps://chs-nhlbi.org/node/668602458nas a2200457 4500008004100000022001400041245012100055210006900176260000900245300001300254490000700267520116800274653002001442653001701462653001101479653001701490653002401507653003601531100001301567700001301580700001801593700001901611700001701630700002001647700002401667700001801691700002101709700001901730700002101749700002301770700001601793700002501809700002001834700001701854700001201871700002201883700001701905700002101922700002101943856003601964 2015 eng d a1932-620300aPopulation genomic analysis of 962 whole genome sequences of humans reveals natural selection in non-coding regions.0 aPopulation genomic analysis of 962 whole genome sequences of hum c2015 ae01216440 v103 aWhole genome analysis in large samples from a single population is needed to provide adequate power to assess relative strengths of natural selection across different functional components of the genome. In this study, we analyzed next-generation sequencing data from 962 European Americans, and found that as expected approximately 60% of the top 1% of positive selection signals lie in intergenic regions, 33% in intronic regions, and slightly over 1% in coding regions. Several detailed functional annotation categories in intergenic regions showed statistically significant enrichment in positively selected loci when compared to the null distribution of the genomic span of ENCODE categories. There was a significant enrichment of purifying selection signals detected in enhancers, transcription factor binding sites, microRNAs and target sites, but not on lincRNA or piRNAs, suggesting different evolutionary constraints for these domains. Loci in "repressed or low activity regions" and loci near or overlapping the transcription start site were the most significantly over-represented annotations among the top 1% of signals for positive selection.
10aDNA, Intergenic10aGenetic Loci10aHumans10aMetagenomics10aOpen Reading Frames10aPolymorphism, Single Nucleotide1 aYu, Fuli1 aLu, Jian1 aLiu, Xiaoming1 aGazave, Elodie1 aChang, Diana1 aRaj, Srilakshmi1 aHunter-Zinck, Haley1 aBlekhman, Ran1 aArbiza, Leonardo1 aVan Hout, Cris1 aMorrison, Alanna1 aJohnson, Andrew, D1 aBis, Joshua1 aCupples, Adrienne, L1 aPsaty, Bruce, M1 aMuzny, Donna1 aYu, Jin1 aGibbs, Richard, A1 aKeinan, Alon1 aClark, Andrew, G1 aBoerwinkle, Eric uhttps://chs-nhlbi.org/node/681404841nas a2200685 4500008004100000022001400041245011900055210006900174260001300243300001000256490000700266520281800273653000903091653001903100653001003119653001103129653003803140653002203178653003403200653001103234653000903245653001603254653002003270653005303290653002103343653002403364653002803388653001103416653001803427100001803445700001603463700002203479700002503501700002003526700002003546700002403566700002403590700002803614700001903642700001803661700002503679700002403704700002003728700001603748700001203764700002403776700002003800700001903820700002903839700002103868700002103889700002203910700002503932700002503957700002603982700001904008700002104027710007104048856003604119 2015 eng d a2168-615700aRare and Coding Region Genetic Variants Associated With Risk of Ischemic Stroke: The NHLBI Exome Sequence Project.0 aRare and Coding Region Genetic Variants Associated With Risk of c2015 Jul a781-80 v723 aIMPORTANCE: Stroke is the second leading cause of death and the third leading cause of years of life lost. Genetic factors contribute to stroke prevalence, and candidate gene and genome-wide association studies (GWAS) have identified variants associated with ischemic stroke risk. These variants often have small effects without obvious biological significance. Exome sequencing may discover predicted protein-altering variants with a potentially large effect on ischemic stroke risk.
OBJECTIVE: To investigate the contribution of rare and common genetic variants to ischemic stroke risk by targeting the protein-coding regions of the human genome.
DESIGN, SETTING, AND PARTICIPANTS: The National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP) analyzed approximately 6000 participants from numerous cohorts of European and African ancestry. For discovery, 365 cases of ischemic stroke (small-vessel and large-vessel subtypes) and 809 European ancestry controls were sequenced; for replication, 47 affected sibpairs concordant for stroke subtype and an African American case-control series were sequenced, with 1672 cases and 4509 European ancestry controls genotyped. The ESP's exome sequencing and genotyping started on January 1, 2010, and continued through June 30, 2012. Analyses were conducted on the full data set between July 12, 2012, and July 13, 2013.
MAIN OUTCOMES AND MEASURES: Discovery of new variants or genes contributing to ischemic stroke risk and subtype (primary analysis) and determination of support for protein-coding variants contributing to risk in previously published candidate genes (secondary analysis).
RESULTS: We identified 2 novel genes associated with an increased risk of ischemic stroke: a protein-coding variant in PDE4DIP (rs1778155; odds ratio, 2.15; P = 2.63 × 10(-8)) with an intracellular signal transduction mechanism and in ACOT4 (rs35724886; odds ratio, 2.04; P = 1.24 × 10(-7)) with a fatty acid metabolism; confirmation of PDE4DIP was observed in affected sibpair families with large-vessel stroke subtype and in African Americans. Replication of protein-coding variants in candidate genes was observed for 2 previously reported GWAS associations: ZFHX3 (cardioembolic stroke) and ABCA1 (large-vessel stroke).
CONCLUSIONS AND RELEVANCE: Exome sequencing discovered 2 novel genes and mechanisms, PDE4DIP and ACOT4, associated with increased risk for ischemic stroke. In addition, ZFHX3 and ABCA1 were discovered to have protein-coding variants associated with ischemic stroke. These results suggest that genetic variation in novel pathways contributes to ischemic stroke risk and serves as a target for prediction, prevention, and therapy.
10aAged10aBrain Ischemia10aExome10aFemale10aGenetic Predisposition to Disease10aGenetic Variation10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aMuscle Proteins10aNational Heart, Lung, and Blood Institute (U.S.)10aNuclear Proteins10aOpen Reading Frames10aPalmitoyl-CoA Hydrolase10aStroke10aUnited States1 aAuer, Paul, L1 aNalls, Mike1 aMeschia, James, F1 aWorrall, Bradford, B1 aLongstreth, W T1 aSeshadri, Sudha1 aKooperberg, Charles1 aBurger, Kathleen, M1 aCarlson, Christopher, S1 aCarty, Cara, L1 aChen, Wei-Min1 aCupples, Adrienne, L1 aDeStefano, Anita, L1 aFornage, Myriam1 aHardy, John1 aHsu, Li1 aJackson, Rebecca, D1 aJarvik, Gail, P1 aKim, Daniel, S1 aLakshminarayan, Kamakshi1 aLange, Leslie, A1 aManichaikul, Ani1 aQuinlan, Aaron, R1 aSingleton, Andrew, B1 aThornton, Timothy, A1 aNickerson, Deborah, A1 aPeters, Ulrike1 aRich, Stephen, S1 aNational Heart, Lung, and Blood Institute Exome Sequencing Project uhttps://chs-nhlbi.org/node/684903793nas a2200553 4500008004100000022001400041245013800055210006900193260001500262300001200277490000700289520217800296100001902474700001802493700002002511700001902531700002002550700001502570700003002585700002302615700002102638700002302659700002402682700002302706700001902729700002002748700002202768700001802790700001902808700002302827700002502850700001702875700002102892700001702913700002402930700002002954700002002974700001802994700001703012700002103029700001903050700002103069700002903090700002103119700002103140700002003161700002203181856003603203 2016 eng d a1558-359700aDiagnostic Yield and Clinical Utility of Sequencing Familial Hypercholesterolemia Genes in Patients With Severe Hypercholesterolemia.0 aDiagnostic Yield and Clinical Utility of Sequencing Familial Hyp c2016 Jun 7 a2578-890 v673 aBACKGROUND: Approximately 7% of American adults have severe hypercholesterolemia (untreated low-density lipoprotein [LDL] cholesterol ≥190 mg/dl), which may be due to familial hypercholesterolemia (FH). Lifelong LDL cholesterol elevations in FH mutation carriers may confer coronary artery disease (CAD) risk beyond that captured by a single LDL cholesterol measurement.
OBJECTIVES: This study assessed the prevalence of an FH mutation among those with severe hypercholesterolemia and determined whether CAD risk varies according to mutation status beyond the observed LDL cholesterol level.
METHODS: Three genes causative for FH (LDLR, APOB, and PCSK9) were sequenced in 26,025 participants from 7 case-control studies (5,540 CAD case subjects, 8,577 CAD-free control subjects) and 5 prospective cohort studies (11,908 participants). FH mutations included loss-of-function variants in LDLR, missense mutations in LDLR predicted to be damaging, and variants linked to FH in ClinVar, a clinical genetics database.
RESULTS: Among 20,485 CAD-free control and prospective cohort participants, 1,386 (6.7%) had LDL cholesterol ≥190 mg/dl; of these, only 24 (1.7%) carried an FH mutation. Within any stratum of observed LDL cholesterol, risk of CAD was higher among FH mutation carriers than noncarriers. Compared with a reference group with LDL cholesterol <130 mg/dl and no mutation, participants with LDL cholesterol ≥190 mg/dl and no FH mutation had a 6-fold higher risk for CAD (odds ratio: 6.0; 95% confidence interval: 5.2 to 6.9), whereas those with both LDL cholesterol ≥190 mg/dl and an FH mutation demonstrated a 22-fold increased risk (odds ratio: 22.3; 95% confidence interval: 10.7 to 53.2). In an analysis of participants with serial lipid measurements over many years, FH mutation carriers had higher cumulative exposure to LDL cholesterol than noncarriers.
CONCLUSIONS: Among participants with LDL cholesterol ≥190 mg/dl, gene sequencing identified an FH mutation in <2%. However, for any observed LDL cholesterol, FH mutation carriers had substantially increased risk for CAD.
1 aKhera, Amit, V1 aWon, Hong-Hee1 aPeloso, Gina, M1 aLawson, Kim, S1 aBartz, Traci, M1 aDeng, Xuan1 avan Leeuwen, Elisabeth, M1 aNatarajan, Pradeep1 aEmdin, Connor, A1 aBick, Alexander, G1 aMorrison, Alanna, C1 aBrody, Jennifer, A1 aGupta, Namrata1 aNomura, Akihiro1 aKessler, Thorsten1 aDuga, Stefano1 aBis, Joshua, C1 aDuijn, Cornelia, M1 aCupples, Adrienne, L1 aPsaty, Bruce1 aRader, Daniel, J1 aDanesh, John1 aSchunkert, Heribert1 aMcPherson, Ruth1 aFarrall, Martin1 aWatkins, Hugh1 aLander, Eric1 aWilson, James, G1 aCorrea, Adolfo1 aBoerwinkle, Eric1 aMerlini, Piera, Angelica1 aArdissino, Diego1 aSaleheen, Danish1 aGabriel, Stacey1 aKathiresan, Sekar uhttps://chs-nhlbi.org/node/701003786nas a2200841 4500008004100000022001400041245009800055210006900153260001300222300001300235490000700248520140700255100001801662700002101680700002401701700002801725700002001753700001901773700001801792700001801810700002001828700002301848700001901871700002001890700001801910700001901928700001801947700002201965700001701987700002502004700002002029700001902049700002102068700002102089700002302110700002402133700002002157700001402177700001402191700001602205700002202221700001502243700002602258700002802284700001702312700002102329700001902350700002602369700002802395700002002423700002402443700002602467700001902493700001702512700001702529700002002546700002502566700001902591700001802610700002102628700002102649700002102670700002902691700001802720700002702738700002302765700002302788710002602811710002302837710002202860710002602882856003602908 2016 eng d a1553-740400aDiscovery of Genetic Variation on Chromosome 5q22 Associated with Mortality in Heart Failure.0 aDiscovery of Genetic Variation on Chromosome 5q22 Associated wit c2016 May ae10060340 v123 aFailure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinants of mortality in patients with new-onset heart failure, we performed a meta-analysis of genome-wide association studies and follow-up genotyping in independent populations. We identified and replicated an association for a genetic variant on chromosome 5q22 with 36% increased risk of death in subjects with heart failure (rs9885413, P = 2.7x10-9). We provide evidence from reporter gene assays, computational predictions and epigenomic marks that this polymorphism increases activity of an enhancer region active in multiple human tissues. The polymorphism was further reproducibly associated with a DNA methylation signature in whole blood (P = 4.5x10-40) that also associated with allergic sensitization and expression in blood of the cytokine TSLP (P = 1.1x10-4). Knockdown of the transcription factor predicted to bind the enhancer region (NHLH1) in a human cell line (HEK293) expressing NHLH1 resulted in lower TSLP expression. In addition, we observed evidence of recent positive selection acting on the risk allele in populations of African descent. Our findings provide novel genetic leads to factors that influence mortality in patients with heart failure.
1 aSmith, Gustav1 aFelix, Janine, F1 aMorrison, Alanna, C1 aKalogeropoulos, Andreas1 aTrompet, Stella1 aWilk, Jemma, B1 aGidlöf, Olof1 aWang, Xinchen1 aMorley, Michael1 aMendelson, Michael1 aJoehanes, Roby1 aLigthart, Symen1 aShan, Xiaoyin1 aBis, Joshua, C1 aWang, Ying, A1 aSjögren, Marketa1 aNgwa, Julius1 aBrandimarto, Jeffrey1 aStott, David, J1 aAguilar, David1 aRice, Kenneth, M1 aSesso, Howard, D1 aDemissie, Serkalem1 aBuckley, Brendan, M1 aTaylor, Kent, D1 aFord, Ian1 aYao, Chen1 aLiu, Chunyu1 aSotoodehnia, Nona1 aHarst, Pim1 aStricker, Bruno, H Ch1 aKritchevsky, Stephen, B1 aLiu, Yongmei1 aGaziano, Michael1 aHofman, Albert1 aMoravec, Christine, S1 aUitterlinden, André, G1 aKellis, Manolis1 avan Meurs, Joyce, B1 aMargulies, Kenneth, B1 aDehghan, Abbas1 aLevy, Daniel1 aOlde, Björn1 aPsaty, Bruce, M1 aCupples, Adrienne, L1 aJukema, Wouter1 aDjoussé, Luc1 aFranco, Oscar, H1 aBoerwinkle, Eric1 aBoyer, Laurie, A1 aNewton-Cheh, Christopher1 aButler, Javed1 aVasan, Ramachandran, S1 aCappola, Thomas, P1 aSmith, Nicholas, L1 aCHARGE-SCD consortium1 aEchoGen consortium1 aQT-IGC consortium1 aCHARGE-QRS consortium uhttps://chs-nhlbi.org/node/714404238nas a2200829 4500008004100000022001400041245019000055210006900245260001300314300001100327490000700338520184100345100001802186700002302204700002202227700002002249700002402269700002202293700002102315700002102336700002202357700002402379700002002403700001502423700002102438700002002459700002002479700002202499700001902521700002102540700001602561700002102577700001902598700002502617700001502642700002402657700001702681700002402698700002002722700002502742700002502767700002002792700002002812700001702832700001702849700002102866700002002887700001902907700001802926700002102944700001702965700001902982700002203001700001903023700002403042700002003066700001603086700002103102700002303123700002003146700002303166700002003189700001903209700001903228700001803247700001803265700002303283700002003306700002103326700002503347856003603372 2016 eng d a1098-227200aAn Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group.0 aEmpirical Comparison of Joint and Stratified Frameworks for Stud c2016 Jul a404-150 v403 aStudying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.
1 aSung, Yun, Ju1 aWinkler, Thomas, W1 aManning, Alisa, K1 aAschard, Hugues1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aSmith, Albert, V1 aBoerwinkle, Eric1 aBrown, Michael, R1 aMorrison, Alanna, C1 aFornage, Myriam1 aLin, Li-An1 aRichard, Melissa1 aBartz, Traci, M1 aPsaty, Bruce, M1 aHayward, Caroline1 aPolasek, Ozren1 aMarten, Jonathan1 aRudan, Igor1 aFeitosa, Mary, F1 aKraja, Aldi, T1 aProvince, Michael, A1 aDeng, Xuan1 aFisher, Virginia, A1 aZhou, Yanhua1 aBielak, Lawrence, F1 aSmith, Jennifer1 aHuffman, Jennifer, E1 aPadmanabhan, Sandosh1 aSmith, Blair, H1 aDing, Jingzhong1 aLiu, Yongmei1 aLohman, Kurt1 aBouchard, Claude1 aRankinen, Tuomo1 aRice, Treva, K1 aArnett, Donna1 aSchwander, Karen1 aGuo, Xiuqing1 aPalmas, Walter1 aRotter, Jerome, I1 aAlfred, Tamuno1 aBottinger, Erwin, P1 aLoos, Ruth, J F1 aAmin, Najaf1 aFranco, Oscar, H1 aDuijn, Cornelia, M1 aVojinovic, Dina1 aChasman, Daniel, I1 aRidker, Paul, M1 aRose, Lynda, M1 aKardia, Sharon1 aZhu, Xiaofeng1 aRice, Kenneth1 aBorecki, Ingrid, B1 aRao, Dabeeru, C1 aGauderman, James1 aCupples, Adrienne, L uhttps://chs-nhlbi.org/node/714505079nas a2201093 4500008004100000022001400041245015000055210006900205260000900274300001300283490000700296520193900303653000902242653001902251653002502270653002802295653001102323653003802334653003402372653001102406653000902417653001602426653002602442653003602468653002402504100001902528700001902547700002202566700002602588700002402614700002502638700002002663700002302683700001902706700001702725700002402742700002002766700002202786700002102808700002802829700002302857700001402880700001802894700002002912700002802932700002402960700002702984700002303011700001903034700001903053700002303072700002203095700002403117700002303141700002003164700002403184700002303208700001803231700002403249700002103273700002403294700002003318700001603338700001503354700002203369700001903391700002003410700001903430700001703449700002203466700001903488700002603507700001903533700002003552700001803572700002403590700001703614700002003631700002603651700002203677700001703699700001703716700001803733700001903751700001903770700002003789700002403809700002103833700002403854700002003878700002103898700003003919856003603949 2016 eng d a1932-620300aGenome-Wide Association Study for Incident Myocardial Infarction and Coronary Heart Disease in Prospective Cohort Studies: The CHARGE Consortium.0 aGenomeWide Association Study for Incident Myocardial Infarction c2016 ae01449970 v113 aBACKGROUND: Data are limited on genome-wide association studies (GWAS) for incident coronary heart disease (CHD). Moreover, it is not known whether genetic variants identified to date also associate with risk of CHD in a prospective setting.
METHODS: We performed a two-stage GWAS analysis of incident myocardial infarction (MI) and CHD in a total of 64,297 individuals (including 3898 MI cases, 5465 CHD cases). SNPs that passed an arbitrary threshold of 5×10-6 in Stage I were taken to Stage II for further discovery. Furthermore, in an analysis of prognosis, we studied whether known SNPs from former GWAS were associated with total mortality in individuals who experienced MI during follow-up.
RESULTS: In Stage I 15 loci passed the threshold of 5×10-6; 8 loci for MI and 8 loci for CHD, for which one locus overlapped and none were reported in previous GWAS meta-analyses. We took 60 SNPs representing these 15 loci to Stage II of discovery. Four SNPs near QKI showed nominally significant association with MI (p-value<8.8×10-3) and three exceeded the genome-wide significance threshold when Stage I and Stage II results were combined (top SNP rs6941513: p = 6.2×10-9). Despite excellent power, the 9p21 locus SNP (rs1333049) was only modestly associated with MI (HR = 1.09, p-value = 0.02) and marginally with CHD (HR = 1.06, p-value = 0.08). Among an inception cohort of those who experienced MI during follow-up, the risk allele of rs1333049 was associated with a decreased risk of subsequent mortality (HR = 0.90, p-value = 3.2×10-3).
CONCLUSIONS: QKI represents a novel locus that may serve as a predictor of incident CHD in prospective studies. The association of the 9p21 locus both with increased risk of first myocardial infarction and longer survival after MI highlights the importance of study design in investigating genetic determinants of complex disorders.
10aAged10aCohort Studies10aCooperative Behavior10aCoronary Artery Disease10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aMyocardial Infarction10aPolymorphism, Single Nucleotide10aProspective Studies1 aDehghan, Abbas1 aBis, Joshua, C1 aWhite, Charles, C1 aSmith, Albert, Vernon1 aMorrison, Alanna, C1 aCupples, Adrienne, L1 aTrompet, Stella1 aChasman, Daniel, I1 aLumley, Thomas1 aVölker, Uwe1 aBuckley, Brendan, M1 aDing, Jingzhong1 aJensen, Majken, K1 aFolsom, Aaron, R1 aKritchevsky, Stephen, B1 aGirman, Cynthia, J1 aFord, Ian1 aDörr, Marcus1 aSalomaa, Veikko1 aUitterlinden, André, G1 aEiriksdottir, Gudny1 aVasan, Ramachandran, S1 aFranceschini, Nora1 aCarty, Cara, L1 aVirtamo, Jarmo1 aDemissie, Serkalem1 aAmouyel, Philippe1 aArveiler, Dominique1 aHeckbert, Susan, R1 aFerrieres, Jean1 aDucimetiere, Pierre1 aSmith, Nicholas, L1 aWang, Ying, A1 aSiscovick, David, S1 aRice, Kenneth, M1 aWiklund, Per-Gunnar1 aTaylor, Kent, D1 aEvans, Alun1 aKee, Frank1 aRotter, Jerome, I1 aKarvanen, Juha1 aKuulasmaa, Kari1 aHeiss, Gerardo1 aKraft, Peter1 aLauner, Lenore, J1 aHofman, Albert1 aMarkus, Marcello, R P1 aRose, Lynda, M1 aSilander, Kaisa1 aWagner, Peter1 aBenjamin, Emelia, J1 aLohman, Kurt1 aStott, David, J1 aRivadeneira, Fernando1 aHarris, Tamara, B1 aLevy, Daniel1 aLiu, Yongmei1 aRimm, Eric, B1 aJukema, Wouter1 aVölzke, Henry1 aRidker, Paul, M1 aBlankenberg, Stefan1 aFranco, Oscar, H1 aGudnason, Vilmundur1 aPsaty, Bruce, M1 aBoerwinkle, Eric1 aO'Donnell, Christopher, J uhttps://chs-nhlbi.org/node/700404981nas a2201333 4500008004100000022001400041245015700055210006900212260001300281300001000294490000700304520112400311100003001435700001601465700001901481700002501500700002101525700002101546700002101567700002301588700002001611700001501631700002101646700002401667700001701691700001901708700001801727700001801745700002001763700002001783700001801803700002501821700002801846700002201874700001801896700002701914700002801941700001901969700002101988700001902009700002102028700001902049700002602068700002302094700002802117700002602145700002102171700002202192700002502214700002302239700002102262700002202283700001902305700001802324700002002342700002102362700001602383700001802399700001702417700002202434700002002456700002102476700002202497700002002519700002202539700002002561700002002581700002102601700002702622700002302649700002302672700001402695700002302709700002802732700002302760700002202783700001702805700002402822700002302846700002502869700002602894700002302920700002002943700002902963700002002992700002303012700002003035700002203055700001803077700001503095700001903110700002903129700002303158700002203181700001903203700002003222700002603242700002203268700001903290700002203309700002103331700002103352700002403373700002103397700002003418700002303438700002103461700002203482700002503504700002303529710002703552710003203579856003603611 2016 eng d a1468-624400aMeta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels.0 aMetaanalysis of 49 549 individuals imputed with the 1000 Genomes c2016 Jul a441-90 v533 aBACKGROUND: So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels.
METHODS: We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage.
RESULTS: Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene.
CONCLUSIONS: This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.
1 avan Leeuwen, Elisabeth, M1 aSabo, Aniko1 aBis, Joshua, C1 aHuffman, Jennifer, E1 aManichaikul, Ani1 aSmith, Albert, V1 aFeitosa, Mary, F1 aDemissie, Serkalem1 aJoshi, Peter, K1 aDuan, Qing1 aMarten, Jonathan1 avan Klinken, Jan, B1 aSurakka, Ida1 aNolte, Ilja, M1 aZhang, Weihua1 aMbarek, Hamdi1 aLi-Gao, Ruifang1 aTrompet, Stella1 aVerweij, Niek1 aEvangelou, Evangelos1 aLyytikäinen, Leo-Pekka1 aTayo, Bamidele, O1 aDeelen, Joris1 avan der Most, Peter, J1 avan der Laan, Sander, W1 aArking, Dan, E1 aMorrison, Alanna1 aDehghan, Abbas1 aFranco, Oscar, H1 aHofman, Albert1 aRivadeneira, Fernando1 aSijbrands, Eric, J1 aUitterlinden, André, G1 aMychaleckyj, Josyf, C1 aCampbell, Archie1 aHocking, Lynne, J1 aPadmanabhan, Sandosh1 aBrody, Jennifer, A1 aRice, Kenneth, M1 aWhite, Charles, C1 aHarris, Tamara1 aIsaacs, Aaron1 aCampbell, Harry1 aLange, Leslie, A1 aRudan, Igor1 aKolcic, Ivana1 aNavarro, Pau1 aZemunik, Tatijana1 aSalomaa, Veikko1 aKooner, Angad, S1 aKooner, Jaspal, S1 aLehne, Benjamin1 aScott, William, R1 aTan, Sian-Tsung1 ade Geus, Eco, J1 aMilaneschi, Yuri1 aPenninx, Brenda, W J H1 aWillemsen, Gonneke1 ade Mutsert, Renée1 aFord, Ian1 aGansevoort, Ron, T1 aSegura-Lepe, Marcelo, P1 aRaitakari, Olli, T1 aViikari, Jorma, S1 aNikus, Kjell1 aForrester, Terrence1 aMcKenzie, Colin, A1 ade Craen, Anton, J M1 ade Ruijter, Hester, M1 aPasterkamp, Gerard1 aSnieder, Harold1 aOldehinkel, Albertine, J1 aSlagboom, Eline1 aCooper, Richard, S1 aKähönen, Mika1 aLehtimäki, Terho1 aElliott, Paul1 aHarst, Pim1 aJukema, Wouter1 aMook-Kanamori, Dennis, O1 aBoomsma, Dorret, I1 aChambers, John, C1 aSwertz, Morris1 aRipatti, Samuli1 avan Dijk, Ko, Willems1 aVitart, Veronique1 aPolasek, Ozren1 aHayward, Caroline1 aWilson, James, G1 aWilson, James, F1 aGudnason, Vilmundur1 aRich, Stephen, S1 aPsaty, Bruce, M1 aBorecki, Ingrid, B1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aCupples, Adrienne, L1 aDuijn, Cornelia, M1 aLifeLines Cohort Study1 aCHARGE Lipids Working Group uhttps://chs-nhlbi.org/node/701104724nas a2201189 4500008004100000022001400041245009300055210006900148260001300217300001200230490000700242520135800249100001801607700002101625700002001646700002501666700002201691700001901713700002301732700002801755700002501783700002101808700001701829700001601846700002201862700002101884700001601905700002001921700002101941700002301962700002201985700002102007700002402028700002102052700002402073700001902097700002502116700002402141700002102165700002502186700002402211700002402235700001402259700001702273700002202290700002302312700001902335700001802354700002502372700002302397700001802420700001702438700001902455700002202474700002402496700001702520700002602537700002002563700001802583700003002601700001602631700001802647700002702665700001802692700002102710700002602731700001902757700001702776700002202793700002202815700002002837700002302857700002102880700002202901700001902923700002002942700002302962700001802985700002803003700001603031700002603047700002103073700002203094700002203116700002803138700002203166700002503188700002103213700002403234700001903258700002303277700002003300700002003320700002603340700002203366700002403388700002303412700001903435700002203454700002203476856003603498 2016 eng d a1468-624400aMeta-analysis of genome-wide association studies of HDL cholesterol response to statins.0 aMetaanalysis of genomewide association studies of HDL cholestero c2016 Dec a835-8450 v533 aBACKGROUND: In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation.
METHODS AND RESULTS: We performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p<1×10(-4) from the 16 769 statin-treated participants in the first analysis stage were followed up in an independent group of 10 951 statin-treated individuals, providing a total sample size of 27 720 individuals. The only associations of genome-wide significance (p<5×10(-8)) were between minor alleles at the CETP locus and greater HDL-C response to statin treatment.
CONCLUSIONS: Based on results from this study that included a relatively large sample size, we suggest that CETP may be the only detectable locus with common genetic variants that influence HDL-C response to statins substantially in individuals of European descent. Although CETP is known to be associated with HDL-C, we provide evidence that this pharmacogenetic effect is independent of its association with baseline HDL-C levels.
1 aPostmus, Iris1 aWarren, Helen, R1 aTrompet, Stella1 aArsenault, Benoit, J1 aAvery, Christy, L1 aBis, Joshua, C1 aChasman, Daniel, I1 ade Keyser, Catherine, E1 aDeshmukh, Harshal, A1 aEvans, Daniel, S1 aFeng, QiPing1 aLi, Xiaohui1 aSmit, Roelof, A J1 aSmith, Albert, V1 aSun, Fangui1 aTaylor, Kent, D1 aArnold, Alice, M1 aBarnes, Michael, R1 aBarratt, Bryan, J1 aBetteridge, John1 aBoekholdt, Matthijs1 aBoerwinkle, Eric1 aBuckley, Brendan, M1 aChen, Y-D, Ida1 ade Craen, Anton, J M1 aCummings, Steven, R1 aDenny, Joshua, C1 aDubé, Marie, Pierre1 aDurrington, Paul, N1 aEiriksdottir, Gudny1 aFord, Ian1 aGuo, Xiuqing1 aHarris, Tamara, B1 aHeckbert, Susan, R1 aHofman, Albert1 aHovingh, Kees1 aKastelein, John, J P1 aLauner, Leonore, J1 aLiu, Ching-Ti1 aLiu, Yongmei1 aLumley, Thomas1 aMcKeigue, Paul, M1 aMunroe, Patricia, B1 aNeil, Andrew1 aNickerson, Deborah, A1 aNyberg, Fredrik1 aO'Brien, Eoin1 aO'Donnell, Christopher, J1 aPost, Wendy1 aPoulter, Neil1 aVasan, Ramachandran, S1 aRice, Kenneth1 aRich, Stephen, S1 aRivadeneira, Fernando1 aSattar, Naveed1 aSever, Peter1 aShaw-Hawkins, Sue1 aShields, Denis, C1 aSlagboom, Eline1 aSmith, Nicholas, L1 aSmith, Joshua, D1 aSotoodehnia, Nona1 aStanton, Alice1 aStott, David, J1 aStricker, Bruno, H1 aStürmer, Til1 aUitterlinden, André, G1 aWei, Wei-Qi1 aWestendorp, Rudi, G J1 aWhitsel, Eric, A1 aWiggins, Kerri, L1 aWilke, Russell, A1 aBallantyne, Christie, M1 aColhoun, Helen, M1 aCupples, Adrienne, L1 aFranco, Oscar, H1 aGudnason, Vilmundur1 aHitman, Graham1 aPalmer, Colin, N A1 aPsaty, Bruce, M1 aRidker, Paul, M1 aStafford, Jeanette, M1 aStein, Charles, M1 aTardif, Jean-Claude1 aCaulfield, Mark, J1 aJukema, Wouter1 aRotter, Jerome, I1 aKrauss, Ronald, M uhttps://chs-nhlbi.org/node/735805480nas a2201321 4500008004100000022001400041245007700055210006900132260001600201520175400217100002301971700001901994700002402013700001902037700001802056700002102074700002302095700001702118700002002135700001802155700001702173700002002190700002002210700002802230700002502258700001802283700002402301700001702325700002402342700002102366700002002387700001902407700001302426700003102439700001602470700001702486700002302503700001802526700002202544700002502566700002002591700002102611700001902632700001902651700002102670700002102691700002202712700002202734700002302756700001902779700001802798700001902816700001802835700001902853700002002872700002402892700001902916700002202935700002002957700001902977700002502996700002203021700002303043700002003066700002303086700001903109700002603128700002203154700002103176700002003197700001603217700002503233700002303258700002303281700002203304700002603326700002103352700002203373700002003395700002203415700002003437700002303457700002803480700002203508700002203530700001703552700002303569700002503592700001803617700002403635700002103659700002103680700002103701700002203722700001803744700001903762700002203781700002403803700002203827700002003849700002903869700002003898700002103918700002203939700002103961700002303982700001904005700002204024700002404046700003004070710002204100856003604122 2016 eng d a1942-326800aMultiethnic Exome-Wide Association Study of Subclinical Atherosclerosis.0 aMultiethnic ExomeWide Association Study of Subclinical Atheroscl c2016 Nov 213 aBACKGROUND: -The burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease (CHD). We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent CHD.
METHODS AND RESULTS: -We studied a total of 25,109 European ancestry and African-American participants with coronary artery calcification (CAC) measured by cardiac computed tomography and 52,869 with common carotid intima media thickness (CIMT) measured by ultrasonography within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Participants were genotyped for 247,870 DNA sequence variants (231,539 in exons) across the genome. A meta-analysis of exome-wide association studies was performed across cohorts for CAC and CIMT. APOB p.Arg3527Gln was associated with four-fold excess CAC (P = 3×10(-10)). The APOE ε2 allele (p.Arg176Cys) was associated with both 22.3% reduced CAC (P = 1×10(-12)) and 1.4% reduced CIMT (P = 4×10(-14)) in carriers compared with non-carriers. In secondary analyses conditioning on LDL cholesterol concentration, the ε2 protective association with CAC, although attenuated, remained strongly significant. Additionally, the presence of ε2 was associated with reduced risk for CHD (OR 0.77; P = 1×10(-11)).
CONCLUSIONS: -Exome-wide association meta-analysis demonstrates that protein-coding variants in APOB and APOE associate with subclinical atherosclerosis. APOE ε2 represents the first significant association for multiple subclinical atherosclerosis traits across multiple ethnicities as well as clinical CHD.
1 aNatarajan, Pradeep1 aBis, Joshua, C1 aBielak, Lawrence, F1 aCox, Amanda, J1 aDörr, Marcus1 aFeitosa, Mary, F1 aFranceschini, Nora1 aGuo, Xiuqing1 aHwang, Shih-Jen1 aIsaacs, Aaron1 aJhun, Min, A1 aKavousi, Maryam1 aLi-Gao, Ruifang1 aLyytikäinen, Leo-Pekka1 aMarioni, Riccardo, E1 aSchminke, Ulf1 aStitziel, Nathan, O1 aTada, Hayato1 avan Setten, Jessica1 aSmith, Albert, V1 aVojinovic, Dina1 aYanek, Lisa, R1 aYao, Jie1 aYerges-Armstrong, Laura, M1 aAmin, Najaf1 aBaber, Usman1 aBorecki, Ingrid, B1 aCarr, Jeffrey1 aChen, Yii-Der Ida1 aCupples, Adrienne, L1 ade Jong, Pim, A1 ade Koning, Harry1 ade Vos, Bob, D1 aDemirkan, Ayse1 aFuster, Valentin1 aFranco, Oscar, H1 aGoodarzi, Mark, O1 aHarris, Tamara, B1 aHeckbert, Susan, R1 aHeiss, Gerardo1 aHoffmann, Udo1 aHofman, Albert1 aIšgum, Ivana1 aJukema, Wouter1 aKähönen, Mika1 aKardia, Sharon, L R1 aKral, Brian, G1 aLauner, Lenore, J1 aMassaro, Joseph1 aMehran, Roxana1 aMitchell, Braxton, D1 aMosley, Thomas, H1 ade Mutsert, Renée1 aNewman, Anne, B1 aNguyen, Khanh-Dung1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aOudkerk, Matthijs1 aPankow, James, S1 aPeloso, Gina, M1 aPost, Wendy1 aProvince, Michael, A1 aRaffield, Laura, M1 aRaitakari, Olli, T1 aReilly, Dermot, F1 aRivadeneira, Fernando1 aRosendaal, Frits1 aSartori, Samantha1 aTaylor, Kent, D1 aTeumer, Alexander1 aTrompet, Stella1 aTurner, Stephen, T1 aUitterlinden, André, G1 aVaidya, Dhananjay1 avan der Lugt, Aad1 aVölker, Uwe1 aWardlaw, Joanna, M1 aWassel, Christina, L1 aWeiss, Stefan1 aWojczynski, Mary, K1 aBecker, Diane, M1 aBecker, Lewis, C1 aBoerwinkle, Eric1 aBowden, Donald, W1 aDeary, Ian, J1 aDehghan, Abbas1 aFelix, Stephan, B1 aGudnason, Vilmundur1 aLehtimäki, Terho1 aMathias, Rasika1 aMook-Kanamori, Dennis, O1 aPsaty, Bruce, M1 aRader, Daniel, J1 aRotter, Jerome, I1 aWilson, James, G1 aDuijn, Cornelia, M1 aVölzke, Henry1 aKathiresan, Sekar1 aPeyser, Patricia, A1 aO'Donnell, Christopher, J1 aCHARGE Consortium uhttps://chs-nhlbi.org/node/725710963nas a2203529 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2016 eng d a2041-172300aA principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.0 aprincipal component metaanalysis on multiple anthropometric trai c2016 11 23 a133570 v73 aLarge consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
10aAnthropometry10aBody Size10aGenome-Wide Association Study10aGenotype10aHumans10aModels, Genetic10aPrincipal Component Analysis1 aRied, Janina, S1 aM, Janina, Jeff1 aChu, Audrey, Y1 aBragg-Gresham, Jennifer, L1 avan Dongen, Jenny1 aHuffman, Jennifer, E1 aAhluwalia, Tarunveer, S1 aCadby, Gemma1 aEklund, Niina1 aEriksson, Joel1 aEsko, Tõnu1 aFeitosa, Mary, F1 aGoel, Anuj1 aGorski, Mathias1 aHayward, Caroline1 aHeard-Costa, Nancy, L1 aJackson, Anne, U1 aJokinen, Eero1 aKanoni, Stavroula1 aKristiansson, Kati1 aKutalik, Zoltán1 aLahti, Jari1 aLuan, Jian'an1 aMägi, Reedik1 aMahajan, Anubha1 aMangino, Massimo1 aMedina-Gómez, Carolina1 aMonda, Keri, L1 aNolte, Ilja, M1 aPerusse, Louis1 aProkopenko, Inga1 aQi, Lu1 aRose, Lynda, M1 aSalvi, Erika1 aSmith, Megan, T1 aSnieder, Harold1 aStančáková, Alena1 aSung, Yun, Ju1 aTachmazidou, Ioanna1 aTeumer, Alexander1 aThorleifsson, Gudmar1 aHarst, Pim1 aWalker, Ryan, W1 aWang, Sophie, R1 aWild, Sarah, H1 aWillems, Sara, M1 aWong, Andrew1 aZhang, Weihua1 aAlbrecht, Eva1 aAlves, Alexessander, Couto1 aBakker, Stephan, J L1 aBarlassina, Cristina1 aBartz, Traci, M1 aBeilby, John1 aBellis, Claire1 aBergman, Richard, N1 aBergmann, Sven1 aBlangero, John1 aBlüher, Matthias1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aBornstein, Stefan, R1 aBruinenberg, Marcel1 aCampbell, Harry1 aChen, Yii-Der Ida1 aChiang, Charleston, W K1 aChines, Peter, S1 aCollins, Francis, S1 aCucca, Fracensco1 aCupples, Adrienne, L1 aD'Avila, Francesca1 aGeus, Eco, J C1 aDedoussis, George1 aDimitriou, Maria1 aDöring, Angela1 aEriksson, Johan, G1 aFarmaki, Aliki-Eleni1 aFarrall, Martin1 aFerreira, Teresa1 aFischer, Krista1 aForouhi, Nita, G1 aFriedrich, Nele1 aGjesing, Anette, Prior1 aGlorioso, Nicola1 aGraff, Mariaelisa1 aGrallert, Harald1 aGrarup, Niels1 aGräßler, Jürgen1 aGrewal, Jagvir1 aHamsten, Anders1 aHarder, Marie, Neergaard1 aHartman, Catharina, A1 aHassinen, Maija1 aHastie, Nicholas1 aHattersley, Andrew, Tym1 aHavulinna, Aki, S1 aHeliövaara, Markku1 aHillege, Hans1 aHofman, Albert1 aHolmen, Oddgeir1 aHomuth, Georg1 aHottenga, Jouke-Jan1 aHui, Jennie1 aHusemoen, Lise, Lotte1 aHysi, Pirro, G1 aIsaacs, Aaron1 aIttermann, Till1 aJalilzadeh, Shapour1 aJames, Alan, L1 aJørgensen, Torben1 aJousilahti, Pekka1 aJula, Antti1 aJustesen, Johanne, Marie1 aJustice, Anne, E1 aKähönen, Mika1 aKaraleftheri, Maria1 aKhaw, Kay, Tee1 aKeinanen-Kiukaanniemi, Sirkka, M1 aKinnunen, Leena1 aKnekt, Paul, B1 aKoistinen, Heikki, A1 aKolcic, Ivana1 aKooner, Ishminder, K1 aKoskinen, Seppo1 aKovacs, Peter1 aKyriakou, Theodosios1 aLaitinen, Tomi1 aLangenberg, Claudia1 aLewin, Alexandra, M1 aLichtner, Peter1 aLindgren, Cecilia, M1 aLindström, Jaana1 aLinneberg, Allan1 aLorbeer, Roberto1 aLorentzon, Mattias1 aLuben, Robert1 aLyssenko, Valeriya1 aMännistö, Satu1 aManunta, Paolo1 aLeach, Irene, Mateo1 aMcArdle, Wendy, L1 aMcKnight, Barbara1 aMohlke, Karen, L1 aMihailov, Evelin1 aMilani, Lili1 aMills, Rebecca1 aMontasser, May, E1 aMorris, Andrew, P1 aMüller, Gabriele1 aMusk, Arthur, W1 aNarisu, Narisu1 aOng, Ken, K1 aOostra, Ben, A1 aOsmond, Clive1 aPalotie, Aarno1 aPankow, James, S1 aPaternoster, Lavinia1 aPenninx, Brenda, W1 aPichler, Irene1 aPilia, Maria, G1 aPolasek, Ozren1 aPramstaller, Peter, P1 aRaitakari, Olli, T1 aRankinen, Tuomo1 aRao, D, C1 aRayner, Nigel, W1 aRibel-Madsen, Rasmus1 aRice, Treva, K1 aRichards, Marcus1 aRidker, Paul, M1 aRivadeneira, Fernando1 aRyan, Kathy, A1 aSanna, Serena1 aSarzynski, Mark, A1 aScholtens, Salome1 aScott, Robert, A1 aSebert, Sylvain1 aSoutham, Lorraine1 aSparsø, Thomas, Hempel1 aSteinthorsdottir, Valgerdur1 aStirrups, Kathleen1 aStolk, Ronald, P1 aStrauch, Konstantin1 aStringham, Heather, M1 aSwertz, Morris, A1 aSwift, Amy, J1 aTönjes, Anke1 aTsafantakis, Emmanouil1 avan der Most, Peter, J1 avan Vliet-Ostaptchouk, Jana, V1 aVandenput, Liesbeth1 aVartiainen, Erkki1 aVenturini, Cristina1 aVerweij, Niek1 aViikari, Jorma, S1 aVitart, Veronique1 aVohl, Marie-Claude1 aVonk, Judith, M1 aWaeber, Gérard1 aWiden, Elisabeth1 aWillemsen, Gonneke1 aWilsgaard, Tom1 aWinkler, Thomas, W1 aWright, Alan, F1 aYerges-Armstrong, Laura, M1 aZhao, Jing, Hua1 aZillikens, Carola, M1 aBoomsma, Dorret, I1 aBouchard, Claude1 aChambers, John, C1 aChasman, Daniel, I1 aCusi, Daniele1 aGansevoort, Ron, T1 aGieger, Christian1 aHansen, Torben1 aHicks, Andrew, A1 aHu, Frank1 aHveem, Kristian1 aJarvelin, Marjo-Riitta1 aKajantie, Eero1 aKooner, Jaspal, S1 aKuh, Diana1 aKuusisto, Johanna1 aLaakso, Markku1 aLakka, Timo, A1 aLehtimäki, Terho1 aMetspalu, Andres1 aNjølstad, Inger1 aOhlsson, Claes1 aOldehinkel, Albertine, J1 aPalmer, Lyle, J1 aPedersen, Oluf1 aPerola, Markus1 aPeters, Annette1 aPsaty, Bruce, M1 aPuolijoki, Hannu1 aRauramaa, Rainer1 aRudan, Igor1 aSalomaa, Veikko1 aSchwarz, Peter, E H1 aShudiner, Alan, R1 aSmit, Jan, H1 aSørensen, Thorkild, I A1 aSpector, Timothy, D1 aStefansson, Kari1 aStumvoll, Michael1 aTremblay, Angelo1 aTuomilehto, Jaakko1 aUitterlinden, André, G1 aUusitupa, Matti1 aVölker, Uwe1 aVollenweider, Peter1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWilson, James, F1 aZeggini, Eleftheria1 aAbecasis, Goncalo, R1 aBoehnke, Michael1 aBorecki, Ingrid, B1 aDeloukas, Panos1 aDuijn, Cornelia, M1 aFox, Caroline1 aGroop, Leif, C1 aHeid, Iris, M1 aHunter, David, J1 aKaplan, Robert, C1 aMcCarthy, Mark, I1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aSchlessinger, David1 aThorsteinsdottir, Unnur1 aStrachan, David, P1 aFrayling, Timothy1 aHirschhorn, Joel, N1 aMüller-Nurasyid, Martina1 aLoos, Ruth, J F uhttps://chs-nhlbi.org/node/857002216nas a2200397 4500008004100000022001400041245018200055210006900237260001200306300001400318490000700332520093100339653002101270653003801291653001101329653005101340653002101391653003601412653001801448100002101466700001801487700002001505700002301525700001801548700002501566700002301591700002501614700002201639700002201661700001601683700002001699700002201719700002201741700001901763856003601782 2016 eng d a1744-804200aRooted in risk: genetic predisposition for low-density lipoprotein cholesterol level associates with diminished low-density lipoprotein cholesterol response to statin treatment.0 aRooted in risk genetic predisposition for lowdensity lipoprotein c2016 10 a1621-16280 v173 aAIMS: To utilize previously reported lead SNPs for low-density lipoprotein cholesterol (LDL-c) levels to find additional loci of importance to statin response, and examine whether genetic predisposition to LDL-c levels associates with differential statin response.
METHODS: We investigated effects on statin response of 59 LDL-c SNPs, by combining summary level statistics from the Global Lipids Genetics and Genomic Investigation of Statin Therapy consortia.
RESULTS: Lead SNPs for APOE, SORT1 and NPC1L1 were associated with a decreased LDL-c response to statin treatment, as was overall genetic predisposition for increased LDL-c levels as quantified with 59 SNPs, with a 5.4% smaller statin response per standard deviation increase in genetically raised LDL-c levels.
CONCLUSION: Genetic predisposition for increased LDL-c level may decrease efficacy of statin therapy.
10aCholesterol, LDL10aGenetic Predisposition to Disease10aHumans10aHydroxymethylglutaryl-CoA Reductase Inhibitors10aPharmacogenetics10aPolymorphism, Single Nucleotide10aTriglycerides1 aSmit, Roelof, Aj1 aPostmus, Iris1 aTrompet, Stella1 aBarnes, Michael, R1 aWarren, Helen1 aArsenault, Benoit, J1 aChasman, Daniel, I1 aCupples, Adrienne, L1 aHitman, Graham, A1 aKrauss, Ronald, M1 aLi, Xiaohui1 aPsaty, Bruce, M1 aStein, Charles, M1 aRotter, Jerome, I1 aJukema, Wouter uhttps://chs-nhlbi.org/node/857103189nas a2200433 4500008004100000022001400041245005100055210005000106260001300156300001300169490000700182520196300189100002202152700002302174700002502197700002202222700001802244700003002262700001902292700002102311700002202332700001902354700002502373700002102398700002602419700001702445700002002462700002002482700002402502700002202526700002402548700002402572700002302596700001902619700002402638700001902662710003802681856003602719 2016 eng d a1553-740400aWhole Exome Sequencing in Atrial Fibrillation.0 aWhole Exome Sequencing in Atrial Fibrillation c2016 Sep ae10062840 v123 aAtrial fibrillation (AF) is a morbid and heritable arrhythmia. Over 35 genes have been reported to underlie AF, most of which were described in small candidate gene association studies. Replication remains lacking for most, and therefore the contribution of coding variation to AF susceptibility remains poorly understood. We examined whole exome sequencing data in a large community-based sample of 1,734 individuals with and 9,423 without AF from the Framingham Heart Study, Cardiovascular Health Study, Atherosclerosis Risk in Communities Study, and NHLBI-GO Exome Sequencing Project and meta-analyzed the results. We also examined whether genetic variation was enriched in suspected AF genes (N = 37) in AF cases versus controls. The mean age ranged from 59 to 73 years; 8,656 (78%) were of European ancestry. None of the 99,404 common variants evaluated was significantly associated after adjusting for multiple testing. Among the most significantly associated variants was a common (allele frequency = 86%) missense variant in SYNPO2L (rs3812629, p.Pro707Leu, [odds ratio 1.27, 95% confidence interval 1.13-1.43, P = 6.6x10-5]) which lies at a known AF susceptibility locus and is in linkage disequilibrium with a top marker from prior analyses at the locus. We did not observe significant associations between rare variants and AF in gene-based tests. Individuals with AF did not display any statistically significant enrichment for common or rare coding variation in previously implicated AF genes. In conclusion, we did not observe associations between coding genetic variants and AF, suggesting that large-effect coding variation is not the predominant mechanism underlying AF. A coding variant in SYNPO2L requires further evaluation to determine whether it is causally related to AF. Efforts to identify biologically meaningful coding variation underlying AF may require large sample sizes or populations enriched for large genetic effects.
1 aLubitz, Steven, A1 aBrody, Jennifer, A1 aBihlmeyer, Nathan, A1 aRoselli, Carolina1 aWeng, Lu-Chen1 aChristophersen, Ingrid, E1 aAlonso, Alvaro1 aBoerwinkle, Eric1 aGibbs, Richard, A1 aBis, Joshua, C1 aCupples, Adrienne, L1 aMohler, Peter, J1 aNickerson, Deborah, A1 aMuzny, Donna1 aPerez, Marco, V1 aPsaty, Bruce, M1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aLunetta, Kathryn, L1 aBenjamin, Emelia, J1 aHeckbert, Susan, R1 aArking, Dan, E1 aEllinor, Patrick, T1 aLin, Honghuang1 aNHLBI GO Exome Sequencing Project uhttps://chs-nhlbi.org/node/725001904nas a2200577 4500008004100000022001400041245010300055210006900158260001600227300001400243490000700257100002300264700002400287700001900311700002600330700002200356700002500378700002000403700002000423700002400443700002000467700002200487700002700509700001900536700002400555700002300579700002100602700001800623700002200641700002800663700003000691700002100721700002100742700002400763700002300787700002300810700002100833700002500854700002700879700002100906700002200927700002100949700002100970700002000991700002501011710006501036710008501101710005101186710005301237856003601290 2017 eng d a1546-171800aAnalysis commons, a team approach to discovery in a big-data environment for genetic epidemiology.0 aAnalysis commons a team approach to discovery in a bigdata envir c2017 Oct 27 a1560-15630 v491 aBrody, Jennifer, A1 aMorrison, Alanna, C1 aBis, Joshua, C1 aO'Connell, Jeffrey, R1 aBrown, Michael, R1 aHuffman, Jennifer, E1 aAmes, Darren, C1 aCarroll, Andrew1 aConomos, Matthew, P1 aGabriel, Stacey1 aGibbs, Richard, A1 aGogarten, Stephanie, M1 aGupta, Namrata1 aJaquish, Cashell, E1 aJohnson, Andrew, D1 aLewis, Joshua, P1 aLiu, Xiaoming1 aManning, Alisa, K1 aPapanicolaou, George, J1 aPitsillides, Achilleas, N1 aRice, Kenneth, M1 aSalerno, William1 aSitlani, Colleen, M1 aSmith, Nicholas, L1 aHeckbert, Susan, R1 aLaurie, Cathy, C1 aMitchell, Braxton, D1 aVasan, Ramachandran, S1 aRich, Stephen, S1 aRotter, Jerome, I1 aWilson, James, G1 aBoerwinkle, Eric1 aPsaty, Bruce, M1 aCupples, Adrienne, L1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aCohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium1 aTOPMed Hematology and Hemostasis Working Group1 aCHARGE Analysis and Bioinformatics Working Group uhttps://chs-nhlbi.org/node/755306485nas a2201489 4500008004100000022001400041245020200055210006900257260001600326300001300342490000700355520221400362100001902576700002202595700001802617700002102635700001902656700001802675700001902693700001902712700002102731700002402752700001802776700002302794700001902817700002402836700001502860700001702875700002102892700002202913700002002935700002402955700002202979700002203001700002703023700001803050700001803068700002203086700002503108700002703133700002303160700001503183700002403198700002803222700002203250700002003272700002103292700002203313700002103335700002403356700001803380700002403398700002203422700002003444700002303464700002003487700002303507700002003530700002403550700001903574700001703593700001803610700001903628700002003647700001803667700001603685700001203701700002203713700001503735700002203750700002203772700001903794700002203813700001903835700002503854700002203879700002303901700001703924700002403941700002303965700002503988700001604013700001904029700002204048700001904070700001304089700001804102700002304120700002304143700002304166700001704189700001804206700002104224700002204245700002104267700002804288700001804316700001904334700001404353700001504367700002104382700002304403700002404426700002904450700001404479700002304493700002204516700002004538700002204558700002104580700002304601700002204624700002204646700002404668700001204692700002104704700002004725700002204745700002104767700002204788700002504810700002704835700002004862700001904882710005804901856003604959 2017 eng d a1553-740400aDiscovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium.0 aDiscovery and finemapping of adiposity loci using high density i c2017 Apr 21 ae10067190 v133 aGenome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.
1 aC Y Ng, Maggie1 aGraff, Mariaelisa1 aLu, Yingchang1 aJustice, Anne, E1 aMudgal, Poorva1 aLiu, Ching-Ti1 aYoung, Kristin1 aYanek, Lisa, R1 aFeitosa, Mary, F1 aWojczynski, Mary, K1 aRand, Kristin1 aBrody, Jennifer, A1 aCade, Brian, E1 aDimitrov, Latchezar1 aDuan, Qing1 aGuo, Xiuqing1 aLange, Leslie, A1 aNalls, Michael, A1 aOkut, Hayrettin1 aTajuddin, Salman, M1 aTayo, Bamidele, O1 aVedantam, Sailaja1 aBradfield, Jonathan, P1 aChen, Guanjie1 aChen, Wei-Min1 aChesi, Alessandra1 aIrvin, Marguerite, R1 aPadhukasahasram, Badri1 aSmith, Jennifer, A1 aZheng, Wei1 aAllison, Matthew, A1 aAmbrosone, Christine, B1 aBandera, Elisa, V1 aBartz, Traci, M1 aBerndt, Sonja, I1 aBernstein, Leslie1 aBlot, William, J1 aBottinger, Erwin, P1 aCarpten, John1 aChanock, Stephen, J1 aChen, Yii-Der Ida1 aConti, David, V1 aCooper, Richard, S1 aFornage, Myriam1 aFreedman, Barry, I1 aGarcia, Melissa1 aGoodman, Phyllis, J1 aHsu, Yu-Han, H1 aHu, Jennifer1 aHuff, Chad, D1 aIngles, Sue, A1 aJohn, Esther, M1 aKittles, Rick1 aKlein, Eric1 aLi, Jin1 aMcKnight, Barbara1 aNayak, Uma1 aNemesure, Barbara1 aOgunniyi, Adesola1 aOlshan, Andrew1 aPress, Michael, F1 aRohde, Rebecca1 aRybicki, Benjamin, A1 aSalako, Babatunde1 aSanderson, Maureen1 aShao, Yaming1 aSiscovick, David, S1 aStanford, Janet, L1 aStevens, Victoria, L1 aStram, Alex1 aStrom, Sara, S1 aVaidya, Dhananjay1 aWitte, John, S1 aYao, Jie1 aZhu, Xiaofeng1 aZiegler, Regina, G1 aZonderman, Alan, B1 aAdeyemo, Adebowale1 aAmbs, Stefan1 aCushman, Mary1 aFaul, Jessica, D1 aHakonarson, Hakon1 aLevin, Albert, M1 aNathanson, Katherine, L1 aWare, Erin, B1 aWeir, David, R1 aZhao, Wei1 aZhi, Degui1 aArnett, Donna, K1 aGrant, Struan, F A1 aKardia, Sharon, L R1 aOloapde, Olufunmilayo, I1 aRao, D, C1 aRotimi, Charles, N1 aSale, Michèle, M1 aWilliams, Keoki1 aZemel, Babette, S1 aBecker, Diane, M1 aBorecki, Ingrid, B1 aEvans, Michele, K1 aHarris, Tamara, B1 aHirschhorn, Joel, N1 aLi, Yun1 aPatel, Sanjay, R1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aWilson, James, G1 aBowden, Donald, W1 aCupples, Adrienne, L1 aHaiman, Christopher, A1 aLoos, Ruth, J F1 aNorth, Kari, E1 aBone Mineral Density in Childhood Study (BMDCS) Group uhttps://chs-nhlbi.org/node/735209668nas a2203061 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2017 eng d a1546-171800aExome-wide association study of plasma lipids in >300,000 individuals.0 aExomewide association study of plasma lipids in 300000 individua c2017 Dec a1758-17660 v493 aWe screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.
10aCoronary Artery Disease10aDiabetes Mellitus, Type 210aExome10aGenetic Association Studies10aGenetic Predisposition to Disease10aGenetic Variation10aGenotype10aHumans10aLipids10aMacular Degeneration10aPhenotype10aRisk Factors1 aLiu, Dajiang, J1 aPeloso, Gina, M1 aYu, Haojie1 aButterworth, Adam, S1 aWang, Xiao1 aMahajan, Anubha1 aSaleheen, Danish1 aEmdin, Connor1 aAlam, Dewan1 aAlves, Alexessander, Couto1 aAmouyel, Philippe1 aDi Angelantonio, Emanuele1 aArveiler, Dominique1 aAssimes, Themistocles, L1 aAuer, Paul, L1 aBaber, Usman1 aBallantyne, Christie, M1 aBang, Lia, E1 aBenn, Marianne1 aBis, Joshua, C1 aBoehnke, Michael1 aBoerwinkle, Eric1 aBork-Jensen, Jette1 aBottinger, Erwin, P1 aBrandslund, Ivan1 aBrown, Morris1 aBusonero, Fabio1 aCaulfield, Mark, J1 aChambers, John, C1 aChasman, Daniel, I1 aChen, Eugene1 aChen, Yii-Der Ida1 aChowdhury, Raj1 aChristensen, Cramer1 aChu, Audrey, Y1 aConnell, John, M1 aCucca, Francesco1 aCupples, Adrienne, L1 aDamrauer, Scott, M1 aDavies, Gail1 aDeary, Ian, J1 aDedoussis, George1 aDenny, Joshua, C1 aDominiczak, Anna1 aDubé, Marie-Pierre1 aEbeling, Tapani1 aEiriksdottir, Gudny1 aEsko, Tõnu1 aFarmaki, Aliki-Eleni1 aFeitosa, Mary, F1 aFerrario, Marco1 aFerrieres, Jean1 aFord, Ian1 aFornage, Myriam1 aFranks, Paul, W1 aFrayling, Timothy, M1 aFrikke-Schmidt, Ruth1 aFritsche, Lars, G1 aFrossard, Philippe1 aFuster, Valentin1 aGanesh, Santhi, K1 aGao, Wei1 aGarcia, Melissa, E1 aGieger, Christian1 aGiulianini, Franco1 aGoodarzi, Mark, O1 aGrallert, Harald1 aGrarup, Niels1 aGroop, Leif1 aGrove, Megan, L1 aGudnason, Vilmundur1 aHansen, Torben1 aHarris, Tamara, B1 aHayward, Caroline1 aHirschhorn, Joel, N1 aHolmen, Oddgeir, L1 aHuffman, Jennifer1 aHuo, Yong1 aHveem, Kristian1 aJabeen, Sehrish1 aJackson, Anne, U1 aJakobsdottir, Johanna1 aJarvelin, Marjo-Riitta1 aJensen, Gorm, B1 aJørgensen, Marit, E1 aJukema, Wouter1 aJustesen, Johanne, M1 aKamstrup, Pia, R1 aKanoni, Stavroula1 aKarpe, Fredrik1 aKee, Frank1 aKhera, Amit, V1 aKlarin, Derek1 aKoistinen, Heikki, A1 aKooner, Jaspal, S1 aKooperberg, Charles1 aKuulasmaa, Kari1 aKuusisto, Johanna1 aLaakso, Markku1 aLakka, Timo1 aLangenberg, Claudia1 aLangsted, Anne1 aLauner, Lenore, J1 aLauritzen, Torsten1 aLiewald, David, C M1 aLin, Li, An1 aLinneberg, Allan1 aLoos, Ruth, J F1 aLu, Yingchang1 aLu, Xiangfeng1 aMägi, Reedik1 aMälarstig, Anders1 aManichaikul, Ani1 aManning, Alisa, K1 aMäntyselkä, Pekka1 aMarouli, Eirini1 aMasca, Nicholas, G D1 aMaschio, Andrea1 aMeigs, James, B1 aMelander, Olle1 aMetspalu, Andres1 aMorris, Andrew, P1 aMorrison, Alanna, C1 aMulas, Antonella1 aMüller-Nurasyid, Martina1 aMunroe, Patricia, B1 aNeville, Matt, J1 aNielsen, Jonas, B1 aNielsen, Sune, F1 aNordestgaard, Børge, G1 aOrdovas, Jose, M1 aMehran, Roxana1 aO'Donnell, Christoper, J1 aOrho-Melander, Marju1 aMolony, Cliona, M1 aMuntendam, Pieter1 aPadmanabhan, Sandosh1 aPalmer, Colin, N A1 aPasko, Dorota1 aPatel, Aniruddh, P1 aPedersen, Oluf1 aPerola, Markus1 aPeters, Annette1 aPisinger, Charlotta1 aPistis, Giorgio1 aPolasek, Ozren1 aPoulter, Neil1 aPsaty, Bruce, M1 aRader, Daniel, J1 aRasheed, Asif1 aRauramaa, Rainer1 aReilly, Dermot, F1 aReiner, Alex, P1 aRenstrom, Frida1 aRich, Stephen, S1 aRidker, Paul, M1 aRioux, John, D1 aRobertson, Neil, R1 aRoden, Dan, M1 aRotter, Jerome, I1 aRudan, Igor1 aSalomaa, Veikko1 aSamani, Nilesh, J1 aSanna, Serena1 aSattar, Naveed1 aSchmidt, Ellen, M1 aScott, Robert, A1 aSever, Peter1 aSevilla, Raquel, S1 aShaffer, Christian, M1 aSim, Xueling1 aSivapalaratnam, Suthesh1 aSmall, Kerrin, S1 aSmith, Albert, V1 aSmith, Blair, H1 aSomayajula, Sangeetha1 aSoutham, Lorraine1 aSpector, Timothy, D1 aSpeliotes, Elizabeth, K1 aStarr, John, M1 aStirrups, Kathleen, E1 aStitziel, Nathan1 aStrauch, Konstantin1 aStringham, Heather, M1 aSurendran, Praveen1 aTada, Hayato1 aTall, Alan, R1 aTang, Hua1 aTardif, Jean-Claude1 aTaylor, Kent, D1 aTrompet, Stella1 aTsao, Philip, S1 aTuomilehto, Jaakko1 aTybjaerg-Hansen, Anne1 avan Zuydam, Natalie, R1 aVarbo, Anette1 aVarga, Tibor, V1 aVirtamo, Jarmo1 aWaldenberger, Melanie1 aWang, Nan1 aWareham, Nick, J1 aWarren, Helen, R1 aWeeke, Peter, E1 aWeinstock, Joshua1 aWessel, Jennifer1 aWilson, James, G1 aWilson, Peter, W F1 aXu, Ming1 aYaghootkar, Hanieh1 aYoung, Robin1 aZeggini, Eleftheria1 aZhang, He1 aZheng, Neil, S1 aZhang, Weihua1 aZhang, Yan1 aZhou, Wei1 aZhou, Yanhua1 aZoledziewska, Magdalena1 aHowson, Joanna, M M1 aDanesh, John1 aMcCarthy, Mark, I1 aCowan, Chad, A1 aAbecasis, Goncalo1 aDeloukas, Panos1 aMusunuru, Kiran1 aWiller, Cristen, J1 aKathiresan, Sekar1 aCharge Diabetes Working Group1 aEPIC-InterAct Consortium1 aEPIC-CVD Consortium1 aGOLD Consortium1 aVA Million Veteran Program uhttps://chs-nhlbi.org/node/757305076nas a2201081 4500008004100000022001400041245010500055210006900160260000900229300001300238490000700251520207300258653001002331653000902341653001902350653002602369653002602395653001102421653004002432653001102472653003402483653001102517653000902528653001602537653001202553653001802565100002502583700002202608700002402630700001902654700002702673700002102700700002302721700001802744700001602762700002302778700002502801700002602826700002102852700002202873700001902895700002002914700002902934700001102963700001702974700001802991700002203009700001903031700001903050700002003069700001603089700002003105700002103125700002103146700002003167700001603187700002103203700002403224700001903248700001703267700001903284700002003303700002003323700002103343700002103364700003203385700001903417700002803436700002403464700002003488700001903508700002103527700002203548700002003570700001903590700002103609700002003630700001603650700002103666700002303687700002503710700002303735700002803758700002503786700002103811700002103832700002003853700002203873700002303895700002003918700002003938856003603958 2017 eng d a1932-620300aGenome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts.0 aGenomewide association metaanalysis of fish and EPADHA consumpti c2017 ae01864560 v123 aBACKGROUND: Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.
OBJECTIVE: To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.
DESIGN: We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.
RESULTS: Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA.
CONCLUSIONS: These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.
10aAdult10aAged10aCohort Studies10aDocosahexaenoic Acids10aEicosapentaenoic Acid10aEurope10aEuropean Continental Ancestry Group10aFemale10aGenome-Wide Association Study10aHumans10aMale10aMiddle Aged10aSeafood10aUnited States1 aMozaffarian, Dariush1 aDashti, Hassan, S1 aWojczynski, Mary, K1 aChu, Audrey, Y1 aNettleton, Jennifer, A1 aMännistö, Satu1 aKristiansson, Kati1 aReedik, Mägi1 aLahti, Jari1 aHouston, Denise, K1 aCornelis, Marilyn, C1 avan Rooij, Frank, J A1 aDimitriou, Maria1 aKanoni, Stavroula1 aMikkilä, Vera1 aSteffen, Lyn, M1 aOtto, Marcia, C de Olive1 aQi, Lu1 aPsaty, Bruce1 aDjoussé, Luc1 aRotter, Jerome, I1 aHarald, Kennet1 aPerola, Markus1 aRissanen, Harri1 aJula, Antti1 aKrista, Fischer1 aMihailov, Evelin1 aFeitosa, Mary, F1 aNgwa, Julius, S1 aXue, Luting1 aJacques, Paul, F1 aPerälä, Mia-Maria1 aPalotie, Aarno1 aLiu, Yongmei1 aNalls, Nike, A1 aFerrucci, Luigi1 aHernandez, Dena1 aManichaikul, Ani1 aTsai, Michael, Y1 ade Jong, Jessica, C Kiefte-1 aHofman, Albert1 aUitterlinden, André, G1 aRallidis, Loukianos1 aRidker, Paul, M1 aRose, Lynda, M1 aBuring, Julie, E1 aLehtimäki, Terho1 aKähönen, Mika1 aViikari, Jorma1 aLemaitre, Rozenn1 aSalomaa, Veikko1 aKnekt, Paul1 aMetspalu, Andres1 aBorecki, Ingrid, B1 aCupples, Adrienne, L1 aEriksson, Johan, G1 aKritchevsky, Stephen, B1 aBandinelli, Stefania1 aSiscovick, David1 aFranco, Oscar, H1 aDeloukas, Panos1 aDedoussis, George1 aChasman, Daniel, I1 aRaitakari, Olli1 aTanaka, Toshiko uhttps://chs-nhlbi.org/node/757804580nas a2200937 4500008004100000022001400041245022100055210006900276260001300345300001200358490000700370520179400377100002102171700002402192700002202216700002202238700002702260700002202287700002002309700002102329700001602350700002102366700001602387700001202403700002102415700001902436700002302455700001902478700002302497700002102520700002402541700002502565700001502590700002102605700002902626700002202655700002302677700002202700700001902722700002002741700001702761700002202778700001202800700002002812700002102832700001802853700002302871700002302894700002902917700001802946700002502964700002102989700001903010700002503029700002403054700001903078700001703097700002303114700002003137700002403157700002203181700002003203700001803223700002003241700002503261700002803286700002403314700002103338700002403359700001903383700002103402700001703423700002903440700002403469700002203493700002703515700002003542700002303562700002103585856003603606 2017 eng d a1468-624400aA genome-wide interaction analysis of tricyclic/tetracyclic antidepressants and RR and QT intervals: a pharmacogenomics study from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.0 agenomewide interaction analysis of tricyclictetracyclic antidepr c2017 May a313-3230 v543 aBACKGROUND: Increased heart rate and a prolonged QT interval are important risk factors for cardiovascular morbidity and mortality, and can be influenced by the use of various medications, including tricyclic/tetracyclic antidepressants (TCAs). We aim to identify genetic loci that modify the association between TCA use and RR and QT intervals.
METHODS AND RESULTS: We conducted race/ethnic-specific genome-wide interaction analyses (with HapMap phase II imputed reference panel imputation) of TCAs and resting RR and QT intervals in cohorts of European (n=45 706; n=1417 TCA users), African (n=10 235; n=296 TCA users) and Hispanic/Latino (n=13 808; n=147 TCA users) ancestry, adjusted for clinical covariates. Among the populations of European ancestry, two genome-wide significant loci were identified for RR interval: rs6737205 in BRE (β=56.3, pinteraction=3.9e(-9)) and rs9830388 in UBE2E2 (β=25.2, pinteraction=1.7e(-8)). In Hispanic/Latino cohorts, rs2291477 in TGFBR3 significantly modified the association between TCAs and QT intervals (β=9.3, pinteraction=2.55e(-8)). In the meta-analyses of the other ethnicities, these loci either were excluded from the meta-analyses (as part of quality control), or their effects did not reach the level of nominal statistical significance (pinteraction>0.05). No new variants were identified in these ethnicities. No additional loci were identified after inverse-variance-weighted meta-analysis of the three ancestries.
CONCLUSIONS: Among Europeans, TCA interactions with variants in BRE and UBE2E2 were identified in relation to RR intervals. Among Hispanic/Latinos, variants in TGFBR3 modified the relation between TCAs and QT intervals. Future studies are required to confirm our results.
1 aNoordam, Raymond1 aSitlani, Colleen, M1 aAvery, Christy, L1 aStewart, James, D1 aGogarten, Stephanie, M1 aWiggins, Kerri, L1 aTrompet, Stella1 aWarren, Helen, R1 aSun, Fangui1 aEvans, Daniel, S1 aLi, Xiaohui1 aLi, Jin1 aSmith, Albert, V1 aBis, Joshua, C1 aBrody, Jennifer, A1 aBusch, Evan, L1 aCaulfield, Mark, J1 aChen, Yii-der, I1 aCummings, Steven, R1 aCupples, Adrienne, L1 aDuan, Qing1 aFranco, Oscar, H1 aMéndez-Giráldez, Rául1 aHarris, Tamara, B1 aHeckbert, Susan, R1 avan Heemst, Diana1 aHofman, Albert1 aFloyd, James, S1 aKors, Jan, A1 aLauner, Lenore, J1 aLi, Yun1 aLi-Gao, Ruifang1 aLange, Leslie, A1 aLin, Henry, J1 ade Mutsert, Renée1 aNapier, Melanie, D1 aNewton-Cheh, Christopher1 aPoulter, Neil1 aReiner, Alexander, P1 aRice, Kenneth, M1 aRoach, Jeffrey1 aRodriguez, Carlos, J1 aRosendaal, Frits, R1 aSattar, Naveed1 aSever, Peter1 aSeyerle, Amanda, A1 aSlagboom, Eline1 aSoliman, Elsayed, Z1 aSotoodehnia, Nona1 aStott, David, J1 aStürmer, Til1 aTaylor, Kent, D1 aThornton, Timothy, A1 aUitterlinden, André, G1 aWilhelmsen, Kirk, C1 aWilson, James, G1 aGudnason, Vilmundur1 aJukema, Wouter1 aLaurie, Cathy, C1 aLiu, Yongmei1 aMook-Kanamori, Dennis, O1 aMunroe, Patricia, B1 aRotter, Jerome, I1 aVasan, Ramachandran, S1 aPsaty, Bruce, M1 aStricker, Bruno, H1 aWhitsel, Eric, A uhttps://chs-nhlbi.org/node/735304016nas a2200865 4500008004100000022001400041245009800055210006900153260001600222520147500238100002001713700002001733700002201753700002001775700002201795700002201817700002801839700002401867700002101891700001901912700003201931700001701963700002801980700002402008700001602032700002202048700001902070700001902089700002002108700001902128700002102147700002002168700002302188700001902211700002002230700001402250700002302264700001902287700002502306700002102331700002102352700002402373700002902397700002502426700002502451700002302476700002502499700002502524700002102549700002402570700002202594700003202616700002002648700002202668700001902690700002302709700002202732700002902754700002502783700002302808700001902831700001702850700002102867700001902888700002202907700002202929700002802951700002602979700002103005700001803026700002403044700002503068700002103093856003603114 2017 eng d a1613-413300aGenome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent.0 aGenomeWide Interactions with Dairy Intake for Body Mass Index in c2017 Sep 213 aSCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.
METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure.
CONCLUSION: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.
1 aSmith, Caren, E1 aFollis, Jack, L1 aDashti, Hassan, S1 aTanaka, Toshiko1 aGraff, Mariaelisa1 aFretts, Amanda, M1 aKilpeläinen, Tuomas, O1 aWojczynski, Mary, K1 aRichardson, Kris1 aNalls, Mike, A1 aSchulz, Christina-Alexandra1 aLiu, Yongmei1 aFrazier-Wood, Alexis, C1 avan Eekelen, Esther1 aWang, Carol1 ade Vries, Paul, S1 aMikkilä, Vera1 aRohde, Rebecca1 aPsaty, Bruce, M1 aHansen, Torben1 aFeitosa, Mary, F1 aLai, Chao-Qiang1 aHouston, Denise, K1 aFerruci, Luigi1 aEricson, Ulrika1 aWang, Zhe1 ade Mutsert, Renée1 aOddy, Wendy, H1 ade Jonge, Ester, A L1 aSeppälä, Ilkka1 aJustice, Anne, E1 aLemaitre, Rozenn, N1 aSørensen, Thorkild, I A1 aProvince, Michael, A1 aParnell, Laurence, D1 aGarcia, Melissa, E1 aBandinelli, Stefania1 aOrho-Melander, Marju1 aRich, Stephen, S1 aRosendaal, Frits, R1 aPennell, Craig, E1 ade Jong, Jessica, C Kiefte-1 aKähönen, Mika1 aYoung, Kristin, L1 aPedersen, Oluf1 aAslibekyan, Stella1 aRotter, Jerome, I1 aMook-Kanamori, Dennis, O1 aZillikens, Carola, M1 aRaitakari, Olli, T1 aNorth, Kari, E1 aOvervad, Kim1 aArnett, Donna, K1 aHofman, Albert1 aLehtimäki, Terho1 aTjønneland, Anne1 aUitterlinden, André, G1 aRivadeneira, Fernando1 aFranco, Oscar, H1 aGerman, Bruce1 aSiscovick, David, S1 aCupples, Adrienne, L1 aOrdovas, Jose, M uhttps://chs-nhlbi.org/node/758804812nas a2201345 4500008004100000022001400041245014400055210006900199260001600268300001000284490000800294520106400302100002601366700001801392700002101410700001301431700002001444700002001464700002301484700002001507700002001527700001801547700002001565700001701585700002301602700001901625700002301644700001801667700002001685700002101705700002301726700001901749700001901768700002301787700001901810700001801829700001801847700002401865700001801889700002201907700002001929700002101949700002101970700002001991700002202011700002102033700002002054700001402074700002002088700001602108700001902124700002002143700002802163700002102191700001702212700002002229700001402249700002102263700002202284700002302306700001502329700001502344700001802359700002202377700002302399700002202422700001902444700002102463700001202484700002402496700002202520700001702542700002002559700002202579700002202601700002002623700001402643700002202657700002102679700002002700700002002720700002302740700002002763700002202783700002202805700001502827700002302842700002302865700002402888700002202912700001702934700001802951700001802969700001802987700002103005700002103026700001603047700002003063700002103083700002103104700002903125700002103154700002403175700003003199700001903229700002503248700002203273700002203295700002003317700002503337700002003362700002203382710002603404856003603430 2017 eng d a1537-660500aGenome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis.0 aGenomewide Transethnic Metaanalysis Identifies Seven Genetic Loc c2017 Jan 05 a51-630 v1003 aGenome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.
1 avan Rooij, Frank, J A1 aQayyum, Rehan1 aSmith, Albert, V1 aZhou, Yi1 aTrompet, Stella1 aTanaka, Toshiko1 aKeller, Margaux, F1 aChang, Li-Ching1 aSchmidt, Helena1 aYang, Min-Lee1 aChen, Ming-Huei1 aHayes, James1 aJohnson, Andrew, D1 aYanek, Lisa, R1 aMueller, Christian1 aLange, Leslie1 aFloyd, James, S1 aGhanbari, Mohsen1 aZonderman, Alan, B1 aJukema, Wouter1 aHofman, Albert1 aDuijn, Cornelia, M1 aDesch, Karl, C1 aSaba, Yasaman1 aOzel, Ayse, B1 aSnively, Beverly, M1 aWu, Jer-Yuarn1 aSchmidt, Reinhold1 aFornage, Myriam1 aKlein, Robert, J1 aFox, Caroline, S1 aMatsuda, Koichi1 aKamatani, Naoyuki1 aWild, Philipp, S1 aStott, David, J1 aFord, Ian1 aSlagboom, Eline1 aYang, Jaden1 aChu, Audrey, Y1 aLambert, Amy, J1 aUitterlinden, André, G1 aFranco, Oscar, H1 aHofer, Edith1 aGinsburg, David1 aHu, Bella1 aKeating, Brendan1 aSchick, Ursula, M1 aBrody, Jennifer, A1 aLi, Jun, Z1 aChen, Zhao1 aZeller, Tanja1 aGuralnik, Jack, M1 aChasman, Daniel, I1 aPeters, Luanne, L1 aKubo, Michiaki1 aBecker, Diane, M1 aLi, Jin1 aEiriksdottir, Gudny1 aRotter, Jerome, I1 aLevy, Daniel1 aGrossmann, Vera1 aPatel, Kushang, V1 aChen, Chien-Hsiun1 aRidker, Paul, M1 aTang, Hua1 aLauner, Lenore, J1 aRice, Kenneth, M1 aLi-Gao, Ruifang1 aFerrucci, Luigi1 aEvans, Michelle, K1 aChoudhuri, Avik1 aTrompouki, Eirini1 aAbraham, Brian, J1 aYang, Song1 aTakahashi, Atsushi1 aKamatani, Yoichiro1 aKooperberg, Charles1 aHarris, Tamara, B1 aJee, Sun, Ha1 aCoresh, Josef1 aTsai, Fuu-Jen1 aLongo, Dan, L1 aChen, Yuan-Tsong1 aFelix, Janine, F1 aYang, Qiong1 aPsaty, Bruce, M1 aBoerwinkle, Eric1 aBecker, Lewis, C1 aMook-Kanamori, Dennis, O1 aWilson, James, G1 aGudnason, Vilmundur1 aO'Donnell, Christopher, J1 aDehghan, Abbas1 aCupples, Adrienne, L1 aNalls, Michael, A1 aMorris, Andrew, P1 aOkada, Yukinori1 aReiner, Alexander, P1 aZon, Leonard, I1 aGanesh, Santhi, K1 aBioBank Japan Project uhttps://chs-nhlbi.org/node/736402661nas a2200253 4500008004100000022001400041245014400055210006900199260001300268490000700281520182600288100001402114700001702128700002302145700002102168700002002189700002502209700002102234700001802255700002402273700002002297710005402317856003602371 2017 eng d a1942-326800aMultiancestry Study of Gene-Lifestyle Interactions for Cardiovascular Traits in 610 475 Individuals From 124 Cohorts: Design and Rationale.0 aMultiancestry Study of GeneLifestyle Interactions for Cardiovasc c2017 Jun0 v103 aBACKGROUND: Several consortia have pursued genome-wide association studies for identifying novel genetic loci for blood pressure, lipids, hypertension, etc. They demonstrated the power of collaborative research through meta-analysis of study-specific results.
METHODS AND RESULTS: The Gene-Lifestyle Interactions Working Group was formed to facilitate the first large, concerted, multiancestry study to systematically evaluate gene-lifestyle interactions. In stage 1, genome-wide interaction analysis is performed in 53 cohorts with a total of 149 684 individuals from multiple ancestries. In stage 2 involving an additional 71 cohorts with 460 791 individuals from multiple ancestries, focused analysis is performed for a subset of the most promising variants from stage 1. In all, the study involves up to 610 475 individuals. Current focus is on cardiovascular traits including blood pressure and lipids, and lifestyle factors including smoking, alcohol, education (as a surrogate for socioeconomic status), physical activity, psychosocial variables, and sleep. The total sample sizes vary among projects because of missing data. Large-scale gene-lifestyle or more generally gene-environment interaction (G×E) meta-analysis studies can be cumbersome and challenging. This article describes the design and some of the approaches pursued in the interaction projects.
CONCLUSIONS: The Gene-Lifestyle Interactions Working Group provides an excellent framework for understanding the lifestyle context of genetic effects and to identify novel trait loci through analysis of interactions. An important and novel feature of our study is that the gene-lifestyle interaction (G×E) results may improve our knowledge about the underlying mechanisms for novel and already known trait loci.
1 aRao, D, C1 aSung, Yun, J1 aWinkler, Thomas, W1 aSchwander, Karen1 aBorecki, Ingrid1 aCupples, Adrienne, L1 aGauderman, James1 aRice, Kenneth1 aMunroe, Patricia, B1 aPsaty, Bruce, M1 aCHARGE Gene-Lifestyle Interactions Working Group* uhttps://chs-nhlbi.org/node/745003304nas a2200553 4500008004100000022001400041245016300055210006900218260001300287300001200300490000700312520166500319100001801984700002402002700002202026700002102048700001902069700002402088700002502112700001802137700002102155700002402176700002202200700001902222700002502241700002102266700001902287700001802306700002202324700001602346700001702362700001902379700001802398700002002416700002202436700002302458700002402481700002102505700002202526700002002548700001602568700002702584700002102611700002102632700002202653700002102675700001802696856003602714 2017 eng d a1942-326800aPCSK9 Loss-of-Function Variants, Low-Density Lipoprotein Cholesterol, and Risk of Coronary Heart Disease and Stroke: Data From 9 Studies of Blacks and Whites.0 aPCSK9 LossofFunction Variants LowDensity Lipoprotein Cholesterol c2017 Aug ae0016320 v103 aBACKGROUND: PCSK9 loss-of-function (LOF) variants allow for the examination of the effects of lifetime reduced low-density lipoprotein cholesterol (LDL-C) on cardiovascular events. We examined the association of PCSK9 LOF variants with LDL-C and incident coronary heart disease and stroke through a meta-analysis of data from 8 observational cohorts and 1 randomized trial of statin therapy.
METHODS AND RESULTS: These 9 studies together included 17 459 blacks with 403 (2.3%) having at least 1 Y142X or C679X variant and 31 306 whites with 955 (3.1%) having at least 1 R46L variant. Unadjusted odds ratios for associations between PCSK9 LOF variants and incident coronary heart disease (851 events in blacks and 2662 events in whites) and stroke (523 events in blacks and 1660 events in whites) were calculated using pooled Mantel-Haenszel estimates with continuity correction factors. Pooling results across studies using fixed-effects inverse-variance-weighted models, PCSK9 LOF variants were associated with 35 mg/dL (95% confidence interval [CI], 32-39) lower LDL-C in blacks and 13 mg/dL (95% CI, 11-16) lower LDL-C in whites. PCSK9 LOF variants were associated with a pooled odds ratio for coronary heart disease of 0.51 (95% CI, 0.28-0.92) in blacks and 0.82 (95% CI, 0.63-1.06) in whites. PCSK9 LOF variants were not associated with incident stroke (odds ratio, 0.84; 95% CI, 0.48-1.47 in blacks and odds ratio, 1.06; 95% CI, 0.80-1.41 in whites).
CONCLUSIONS: PCSK9 LOF variants were associated with lower LDL-C and coronary heart disease incidence. PCSK9 LOF variants were not associated with stroke risk.
1 aKent, Shia, T1 aRosenson, Robert, S1 aAvery, Christy, L1 aChen, Yii-der, I1 aCorrea, Adolfo1 aCummings, Steven, R1 aCupples, Adrienne, L1 aCushman, Mary1 aEvans, Daniel, S1 aGudnason, Vilmundur1 aHarris, Tamara, B1 aHoward, George1 aIrvin, Marguerite, R1 aJudd, Suzanne, E1 aJukema, Wouter1 aLange, Leslie1 aLevitan, Emily, B1 aLi, Xiaohui1 aLiu, Yongmei1 aPost, Wendy, S1 aPostmus, Iris1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aSafford, Monika, M1 aSitlani, Colleen, M1 aSmith, Albert, V1 aStewart, James, D1 aTrompet, Stella1 aSun, Fangui1 aVasan, Ramachandran, S1 aWoolley, Michael1 aWhitsel, Eric, A1 aWiggins, Kerri, L1 aWilson, James, G1 aMuntner, Paul uhttps://chs-nhlbi.org/node/744817687nas a2205785 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2017 eng d a1546-171800aRare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease.0 aRare coding variants in PLCG2 ABI3 and TREM2 implicate microglia c2017 Sep a1373-13840 v493 aWe identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10-8) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10-10, odds ratio (OR) = 0.68, minor allele frequency (MAF)cases = 0.0059, MAFcontrols = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10-10, OR = 1.43, MAFcases = 0.011, MAFcontrols = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10-14, OR = 1.67, MAFcases = 0.0143, MAFcontrols = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.
10aAdaptor Proteins, Signal Transducing10aAlzheimer Disease10aAmino Acid Sequence10aCase-Control Studies10aExome10aGene Expression Profiling10aGene Frequency10aGenetic Predisposition to Disease10aGenotype10aHumans10aImmunity, Innate10aLinkage Disequilibrium10aMembrane Glycoproteins10aMicroglia10aOdds Ratio10aPhospholipase C gamma10aPolymorphism, Single Nucleotide10aProtein Interaction Maps10aReceptors, Immunologic10aSequence Homology, Amino Acid1 aSims, Rebecca1 avan der Lee, Sven, J1 aNaj, Adam, C1 aBellenguez, Céline1 aBadarinarayan, Nandini1 aJakobsdottir, Johanna1 aKunkle, Brian, W1 aBoland, Anne1 aRaybould, Rachel1 aBis, Joshua, C1 aMartin, Eden, R1 aGrenier-Boley, Benjamin1 aHeilmann-Heimbach, Stefanie1 aChouraki, Vincent1 aKuzma, Amanda, B1 aSleegers, Kristel1 aVronskaya, Maria1 aRuiz, Agustin1 aGraham, Robert, R1 aOlaso, Robert1 aHoffmann, Per1 aGrove, Megan, L1 aVardarajan, Badri, N1 aHiltunen, Mikko1 aNöthen, Markus, M1 aWhite, Charles, C1 aHamilton-Nelson, Kara, L1 aEpelbaum, Jacques1 aMaier, Wolfgang1 aChoi, Seung-Hoan1 aBeecham, Gary, W1 aDulary, Cécile1 aHerms, Stefan1 aSmith, Albert, V1 aFunk, Cory, C1 aDerbois, Céline1 aForstner, Andreas, J1 aAhmad, Shahzad1 aLi, Hongdong1 aBacq, Delphine1 aHarold, Denise1 aSatizabal, Claudia, L1 aValladares, Otto1 aSquassina, Alessio1 aThomas, Rhodri1 aBrody, Jennifer, A1 aQu, Liming1 aSánchez-Juan, Pascual1 aMorgan, Taniesha1 aWolters, Frank, J1 aZhao, Yi1 aGarcia, Florentino, Sanchez1 aDenning, Nicola1 aFornage, Myriam1 aMalamon, John1 aNaranjo, Maria, Candida De1 aMajounie, Elisa1 aMosley, Thomas, H1 aDombroski, Beth1 aWallon, David1 aLupton, Michelle, K1 aDupuis, Josée1 aWhitehead, Patrice1 aFratiglioni, Laura1 aMedway, Christopher1 aJian, Xueqiu1 aMukherjee, Shubhabrata1 aKeller, Lina1 aBrown, Kristelle1 aLin, Honghuang1 aCantwell, Laura, B1 aPanza, Francesco1 aMcGuinness, Bernadette1 aMoreno-Grau, Sonia1 aBurgess, Jeremy, D1 aSolfrizzi, Vincenzo1 aProitsi, Petra1 aAdams, Hieab, H1 aAllen, Mariet1 aSeripa, Davide1 aPastor, Pau1 aCupples, Adrienne, L1 aPrice, Nathan, D1 aHannequin, Didier1 aFrank-García, Ana1 aLevy, Daniel1 aChakrabarty, Paramita1 aCaffarra, Paolo1 aGiegling, Ina1 aBeiser, Alexa, S1 aGiedraitis, Vilmantas1 aHampel, Harald1 aGarcia, Melissa, E1 aWang, Xue1 aLannfelt, Lars1 aMecocci, Patrizia1 aEiriksdottir, Gudny1 aCrane, Paul, K1 aPasquier, Florence1 aBoccardi, Virginia1 aHenández, Isabel1 aBarber, Robert, C1 aScherer, Martin1 aTarraga, Lluis1 aAdams, Perrie, M1 aLeber, Markus1 aChen, Yuning1 aAlbert, Marilyn, S1 aRiedel-Heller, Steffi1 aEmilsson, Valur1 aBeekly, Duane1 aBraae, Anne1 aSchmidt, Reinhold1 aBlacker, Deborah1 aMasullo, Carlo1 aSchmidt, Helena1 aDoody, Rachelle, S1 aSpalletta, Gianfranco1 aJr, W, T Longstre1 aFairchild, Thomas, J1 aBossù, Paola1 aLopez, Oscar, L1 aFrosch, Matthew, P1 aSacchinelli, Eleonora1 aGhetti, Bernardino1 aYang, Qiong1 aHuebinger, Ryan, M1 aJessen, Frank1 aLi, Shuo1 aKamboh, Ilyas1 aMorris, John1 aSotolongo-Grau, Oscar1 aKatz, Mindy, J1 aCorcoran, Chris1 aDunstan, Melanie1 aBraddel, Amy1 aThomas, Charlene1 aMeggy, Alun1 aMarshall, Rachel1 aGerrish, Amy1 aChapman, Jade1 aAguilar, Miquel1 aTaylor, Sarah1 aHill, Matt1 aFairén, Mònica, Díez1 aHodges, Angela1 aVellas, Bruno1 aSoininen, Hilkka1 aKloszewska, Iwona1 aDaniilidou, Makrina1 aUphill, James1 aPatel, Yogen1 aHughes, Joseph, T1 aLord, Jenny1 aTurton, James1 aHartmann, Annette, M1 aCecchetti, Roberta1 aFenoglio, Chiara1 aSerpente, Maria1 aArcaro, Marina1 aCaltagirone, Carlo1 aOrfei, Maria, Donata1 aCiaramella, Antonio1 aPichler, Sabrina1 aMayhaus, Manuel1 aGu, Wei1 aLleo, Alberto1 aFortea, Juan1 aBlesa, Rafael1 aBarber, Imelda, S1 aBrookes, Keeley1 aCupidi, Chiara1 aMaletta, Raffaele, Giovanni1 aCarrell, David1 aSorbi, Sandro1 aMoebus, Susanne1 aUrbano, Maria1 aPilotto, Alberto1 aKornhuber, Johannes1 aBosco, Paolo1 aTodd, Stephen1 aCraig, David1 aJohnston, Janet1 aGill, Michael1 aLawlor, Brian1 aLynch, Aoibhinn1 aFox, Nick, C1 aHardy, John1 aAlbin, Roger, L1 aApostolova, Liana, G1 aArnold, Steven, E1 aAsthana, Sanjay1 aAtwood, Craig, S1 aBaldwin, Clinton, T1 aBarnes, Lisa, L1 aBarral, Sandra1 aBeach, Thomas, G1 aBecker, James, T1 aBigio, Eileen, H1 aBird, Thomas, D1 aBoeve, Bradley, F1 aBowen, James, D1 aBoxer, Adam1 aBurke, James, R1 aBurns, Jeffrey, M1 aBuxbaum, Joseph, D1 aCairns, Nigel, J1 aCao, Chuanhai1 aCarlson, Chris, S1 aCarlsson, Cynthia, M1 aCarney, Regina, M1 aCarrasquillo, Minerva, M1 aCarroll, Steven, L1 aDiaz, Carolina, Ceballos1 aChui, Helena, C1 aClark, David, G1 aCribbs, David, H1 aCrocco, Elizabeth, A1 aDeCarli, Charles1 aDick, Malcolm1 aDuara, Ranjan1 aEvans, Denis, A1 aFaber, Kelley, M1 aFallon, Kenneth, B1 aFardo, David, W1 aFarlow, Martin, R1 aFerris, Steven1 aForoud, Tatiana, M1 aGalasko, Douglas, R1 aGearing, Marla1 aGeschwind, Daniel, H1 aGilbert, John, R1 aGraff-Radford, Neill, R1 aGreen, Robert, C1 aGrowdon, John, H1 aHamilton, Ronald, L1 aHarrell, Lindy, E1 aHonig, Lawrence, S1 aHuentelman, Matthew, J1 aHulette, Christine, M1 aHyman, Bradley, T1 aJarvik, Gail, P1 aAbner, Erin1 aJin, Lee-Way1 aJun, Gyungah1 aKarydas, Anna1 aKaye, Jeffrey, A1 aKim, Ronald1 aKowall, Neil, W1 aKramer, Joel, H1 aLaFerla, Frank, M1 aLah, James, J1 aLeverenz, James, B1 aLevey, Allan, I1 aLi, Ge1 aLieberman, Andrew, P1 aLunetta, Kathryn, L1 aLyketsos, Constantine, G1 aMarson, Daniel, C1 aMartiniuk, Frank1 aMash, Deborah, C1 aMasliah, Eliezer1 aMcCormick, Wayne, C1 aMcCurry, Susan, M1 aMcDavid, Andrew, N1 aMcKee, Ann, C1 aMesulam, Marsel1 aMiller, Bruce, L1 aMiller, Carol, A1 aMiller, Joshua, W1 aMorris, John, C1 aMurrell, Jill, R1 aMyers, Amanda, J1 aO'Bryant, Sid1 aOlichney, John, M1 aPankratz, Vernon, S1 aParisi, Joseph, E1 aPaulson, Henry, L1 aPerry, William1 aPeskind, Elaine1 aPierce, Aimee1 aPoon, Wayne, W1 aPotter, Huntington1 aQuinn, Joseph, F1 aRaj, Ashok1 aRaskind, Murray1 aReisberg, Barry1 aReitz, Christiane1 aRingman, John, M1 aRoberson, Erik, D1 aRogaeva, Ekaterina1 aRosen, Howard, J1 aRosenberg, Roger, N1 aSager, Mark, A1 aSaykin, Andrew, J1 aSchneider, Julie, A1 aSchneider, Lon, S1 aSeeley, William, W1 aSmith, Amanda, G1 aSonnen, Joshua, A1 aSpina, Salvatore1 aStern, Robert, A1 aSwerdlow, Russell, H1 aTanzi, Rudolph, E1 aThornton-Wells, Tricia, A1 aTrojanowski, John, Q1 aTroncoso, Juan, C1 aVan Deerlin, Vivianna, M1 aVan Eldik, Linda, J1 aVinters, Harry, V1 aVonsattel, Jean, Paul1 aWeintraub, Sandra1 aWelsh-Bohmer, Kathleen, A1 aWilhelmsen, Kirk, C1 aWilliamson, Jennifer1 aWingo, Thomas, S1 aWoltjer, Randall, L1 aWright, Clinton, B1 aYu, Chang-En1 aYu, Lei1 aGarzia, Fabienne1 aGolamaully, Feroze1 aSeptier, Gislain1 aEngelborghs, Sebastien1 aVandenberghe, Rik1 aDe Deyn, Peter, P1 aFernadez, Carmen, Muñoz1 aBenito, Yoland, Aladro1 aThonberg, Håkan1 aForsell, Charlotte1 aLilius, Lena1 aKinhult-Ståhlbom, Anne1 aKilander, Lena1 aBrundin, RoseMarie1 aConcari, Letizia1 aHelisalmi, Seppo1 aKoivisto, Anne, Maria1 aHaapasalo, Annakaisa1 aDermecourt, Vincent1 aFiévet, Nathalie1 aHanon, Olivier1 aDufouil, Carole1 aBrice, Alexis1 aRitchie, Karen1 aDubois, Bruno1 aHimali, Jayanadra, J1 aKeene, Dirk1 aTschanz, JoAnn1 aFitzpatrick, Annette, L1 aKukull, Walter, A1 aNorton, Maria1 aAspelund, Thor1 aLarson, Eric, B1 aMunger, Ron1 aRotter, Jerome, I1 aLipton, Richard, B1 aBullido, María, J1 aHofman, Albert1 aMontine, Thomas, J1 aCoto, Eliecer1 aBoerwinkle, Eric1 aPetersen, Ronald, C1 aAlvarez, Victoria1 aRivadeneira, Fernando1 aReiman, Eric, M1 aGallo, Maura1 aO'Donnell, Christopher, J1 aReisch, Joan, S1 aBruni, Amalia, Cecilia1 aRoyall, Donald, R1 aDichgans, Martin1 aSano, Mary1 aGalimberti, Daniela1 aSt George-Hyslop, Peter1 aScarpini, Elio1 aTsuang, Debby, W1 aMancuso, Michelangelo1 aBonuccelli, Ubaldo1 aWinslow, Ashley, R1 aDaniele, Antonio1 aWu, Chuang-Kuo1 aPeters, Oliver1 aNacmias, Benedetta1 aRiemenschneider, Matthias1 aHeun, Reinhard1 aBrayne, Carol1 aRubinsztein, David, C1 aBras, Jose1 aGuerreiro, Rita1 aAl-Chalabi, Ammar1 aShaw, Christopher, E1 aCollinge, John1 aMann, David1 aTsolaki, Magda1 aClarimon, Jordi1 aSussams, Rebecca1 aLovestone, Simon1 aO'Donovan, Michael, C1 aOwen, Michael, J1 aBehrens, Timothy, W1 aMead, Simon1 aGoate, Alison, M1 aUitterlinden, André, G1 aHolmes, Clive1 aCruchaga, Carlos1 aIngelsson, Martin1 aBennett, David, A1 aPowell, John1 aGolde, Todd, E1 aGraff, Caroline1 aDe Jager, Philip, L1 aMorgan, Kevin1 aErtekin-Taner, Nilufer1 aCombarros, Onofre1 aPsaty, Bruce, M1 aPassmore, Peter1 aYounkin, Steven, G1 aBerr, Claudine1 aGudnason, Vilmundur1 aRujescu, Dan1 aDickson, Dennis, W1 aDartigues, Jean-François1 aDeStefano, Anita, L1 aOrtega-Cubero, Sara1 aHakonarson, Hakon1 aCampion, Dominique1 aBoada, Merce1 aKauwe, John, Keoni1 aFarrer, Lindsay, A1 aVan Broeckhoven, Christine1 aIkram, Arfan, M1 aJones, Lesley1 aHaines, Jonathan, L1 aTzourio, Christophe1 aLauner, Lenore, J1 aEscott-Price, Valentina1 aMayeux, Richard1 aDeleuze, Jean-Francois1 aAmin, Najaf1 aHolmans, Peter, A1 aPericak-Vance, Margaret, A1 aAmouyel, Philippe1 aDuijn, Cornelia, M1 aRamirez, Alfredo1 aSan Wang, Li-1 aLambert, Jean-Charles1 aSeshadri, Sudha1 aWilliams, Julie1 aSchellenberg, Gerard, D1 aARUK Consortium1 aGERAD/PERADES, CHARGE, ADGC, EADI uhttps://chs-nhlbi.org/node/758703950nas a2200685 4500008004100000022001400041245009900055210006900154260001300223300001200236490000700248520197400255100002002229700002302249700001902272700002302291700001702314700001902331700002102350700002202371700002202393700001802415700002402433700001902457700001302476700002202489700002102511700001902532700002302551700002402574700001902598700002402617700002502641700001902666700002902685700001802714700002302732700002602755700001902781700002102800700003002821700002202851700002602873700002302899700002302922700002402945700001702969700002202986700002403008700002203032700002503054700002103079700002003100700002003120700002103140700002103161700002203182700002403204856003603228 2018 eng d a2574-830000aCommon Coding Variants in Are Associated With the Nav1.8 Late Current and Cardiac Conduction.0 aCommon Coding Variants in Are Associated With the Nav18 Late Cur c2018 May ae0016630 v113 aBACKGROUND: Genetic variants at the / locus are strongly associated with electrocardiographic PR and QRS intervals. While is the canonical cardiac sodium channel gene, the role of in cardiac conduction is less well characterized.
METHODS: We sequenced the locus in 3699 European-ancestry individuals to identify variants associated with cardiac conduction, and replicated our findings in 21,000 individuals of European ancestry. We examined association with expression in human atrial tissue. We explored the biophysical effect of variation on channel function using cellular electrophysiology.
RESULTS: We identified 2 intronic single nucleotide polymorphisms in high linkage disequilibrium ( =0.86) with each other to be the strongest signals for PR (rs10428132, β=-4.74, =1.52×10) and QRS intervals (rs6599251, QRS β=-0.73; =1.2×10), respectively. Although these variants were not associated with or expression in human atrial tissue (n=490), they were in high linkage disequilibrium ( ≥0.72) with a common missense variant, rs6795970 (V1073A). In total, we identified 7 missense variants, 4 of which (I962V, P1045T, V1073A, and L1092P) were associated with cardiac conduction. These 4 missense variants cluster in the cytoplasmic linker of the second and third domains of the SCN10A protein and together form 6 common haplotypes. Using cellular electrophysiology, we found that haplotypes associated with shorter PR intervals had a significantly larger percentage of late current compared with wild-type (I962V+V1073A+L1092P, 20.2±3.3%, =0.03, and I962V+V1073A, 22.4±0.8%, =0.0004 versus wild-type 11.7±1.6%), and the haplotype associated with the longest PR interval had a significantly smaller late current percentage (P1045T, 6.4±1.2%, =0.03).
CONCLUSIONS: Our findings suggest an association between genetic variation in , the late sodium current, and alterations in cardiac conduction.
1 aMacri, Vincenzo1 aBrody, Jennifer, A1 aArking, Dan, E1 aHucker, William, J1 aYin, Xiaoyan1 aLin, Honghuang1 aMills, Robert, W1 aSinner, Moritz, F1 aLubitz, Steven, A1 aLiu, Ching-Ti1 aMorrison, Alanna, C1 aAlonso, Alvaro1 aLi, Ning1 aFedorov, Vadim, V1 aJanssen, Paul, M1 aBis, Joshua, C1 aHeckbert, Susan, R1 aDolmatova, Elena, V1 aLumley, Thomas1 aSitlani, Colleen, M1 aCupples, Adrienne, L1 aPulit, Sara, L1 aNewton-Cheh, Christopher1 aBarnard, John1 aSmith, Jonathan, D1 aVan Wagoner, David, R1 aChung, Mina, K1 aVlahakes, Gus, J1 aO'Donnell, Christopher, J1 aRotter, Jerome, I1 aMargulies, Kenneth, B1 aMorley, Michael, P1 aCappola, Thomas, P1 aBenjamin, Emelia, J1 aMuzny, Donna1 aGibbs, Richard, A1 aJackson, Rebecca, D1 aMagnani, Jared, W1 aHerndon, Caroline, N1 aRich, Stephen, S1 aPsaty, Bruce, M1 aMilan, David, J1 aBoerwinkle, Eric1 aMohler, Peter, J1 aSotoodehnia, Nona1 aEllinor, Patrick, T uhttps://chs-nhlbi.org/node/780205033nas a2201381 4500008004100000022001400041245013800055210006900193260001600262300000800278490000600286520112300292100001501415700002201430700002001452700001901472700002001491700001901511700002001530700001901550700001701569700001701586700002201603700001901625700001701644700002501661700002701686700002301713700002201736700001201758700001801770700002201788700002501810700001901835700001401854700001701868700002201885700002001907700002101927700002801948700002201976700001801998700002702016700002802043700003102071700001802102700002502120700002002145700002702165700001802192700001702210700002002227700001902247700002402266700002302290700002302313700001502336700002302351700002802374700001702402700002002419700002002439700001902459700002202478700002002500700002002520700001802540700002202558700002202580700002002602700002002622700002002642700002202662700002102684700003002705700002402735700002702759700002002786700002002806700002102826700002202847700001502869700002302884700002002907700002502927700002802952700002602980700001703006700001603023700002003039700002403059700002503083700002103108700002303129700001903152700001903171700002203190700002803212700002003240700002303260700001903283700002003302700001903322700001903341700002503360700002403385700002103409700002503430700001803455700002503473700001703498700002103515700002003536700002103556700001703577700002103594856003603615 2018 eng d a2041-172300aGenome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels.0 aGenomewide association study in 79366 Europeanancestry individua c2018 Jan 17 a2600 v93 aVitamin D is a steroid hormone precursor that is associated with a range of human traits and diseases. Previous GWAS of serum 25-hydroxyvitamin D concentrations have identified four genome-wide significant loci (GC, NADSYN1/DHCR7, CYP2R1, CYP24A1). In this study, we expand the previous SUNLIGHT Consortium GWAS discovery sample size from 16,125 to 79,366 (all European descent). This larger GWAS yields two additional loci harboring genome-wide significant variants (P = 4.7×10 at rs8018720 in SEC23A, and P = 1.9×10 at rs10745742 in AMDHD1). The overall estimate of heritability of 25-hydroxyvitamin D serum concentrations attributable to GWAS common SNPs is 7.5%, with statistically significant loci explaining 38% of this total. Further investigation identifies signal enrichment in immune and hematopoietic tissues, and clustering with autoimmune diseases in cell-type-specific analysis. Larger studies are required to identify additional common SNPs, and to explore the role of rare or structural variants and gene-gene interactions in the heritability of circulating 25-hydroxyvitamin D levels.
1 aJiang, Xia1 aO'Reilly, Paul, F1 aAschard, Hugues1 aHsu, Yi-Hsiang1 aRichards, Brent1 aDupuis, Josée1 aIngelsson, Erik1 aKarasik, David1 aPilz, Stefan1 aBerry, Diane1 aKestenbaum, Bryan1 aZheng, Jusheng1 aLuan, Jianan1 aSofianopoulou, Eleni1 aStreeten, Elizabeth, A1 aAlbanes, Demetrius1 aLutsey, Pamela, L1 aYao, Lu1 aTang, Weihong1 aEcons, Michael, J1 aWallaschofski, Henri1 aVölzke, Henry1 aZhou, Ang1 aPower, Chris1 aMcCarthy, Mark, I1 aMichos, Erin, D1 aBoerwinkle, Eric1 aWeinstein, Stephanie, J1 aFreedman, Neal, D1 aHuang, Wen-Yi1 avan Schoor, Natasja, M1 avan der Velde, Nathalie1 ade Groot, Lisette, C P G M1 aEnneman, Anke1 aCupples, Adrienne, L1 aBooth, Sarah, L1 aVasan, Ramachandran, S1 aLiu, Ching-Ti1 aZhou, Yanhua1 aRipatti, Samuli1 aOhlsson, Claes1 aVandenput, Liesbeth1 aLorentzon, Mattias1 aEriksson, Johan, G1 aShea, Kyla1 aHouston, Denise, K1 aKritchevsky, Stephen, B1 aLiu, Yongmei1 aLohman, Kurt, K1 aFerrucci, Luigi1 aPeacock, Munro1 aGieger, Christian1 aBeekman, Marian1 aSlagboom, Eline1 aDeelen, Joris1 avan Heemst, Diana1 aKleber, Marcus, E1 aMärz, Winfried1 ade Boer, Ian, H1 aWood, Alexis, C1 aRotter, Jerome, I1 aRich, Stephen, S1 aRobinson-Cohen, Cassianne1 aHeijer, Martin, den1 aJarvelin, Marjo-Riitta1 aCavadino, Alana1 aJoshi, Peter, K1 aWilson, James, F1 aHayward, Caroline1 aLind, Lars1 aMichaëlsson, Karl1 aTrompet, Stella1 aZillikens, Carola, M1 aUitterlinden, André, G1 aRivadeneira, Fernando1 aBroer, Linda1 aZgaga, Lina1 aCampbell, Harry1 aTheodoratou, Evropi1 aFarrington, Susan, M1 aTimofeeva, Maria1 aDunlop, Malcolm, G1 aValdes, Ana, M1 aTikkanen, Emmi1 aLehtimäki, Terho1 aLyytikäinen, Leo-Pekka1 aKähönen, Mika1 aRaitakari, Olli, T1 aMikkilä, Vera1 aIkram, Arfan, M1 aSattar, Naveed1 aJukema, Wouter1 aWareham, Nicholas, J1 aLangenberg, Claudia1 aForouhi, Nita, G1 aGundersen, Thomas, E1 aKhaw, Kay-Tee1 aButterworth, Adam, S1 aDanesh, John1 aSpector, Timothy1 aWang, Thomas, J1 aHyppönen, Elina1 aKraft, Peter1 aKiel, Douglas, P uhttps://chs-nhlbi.org/node/766712060nas a2203745 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2018 eng d a1537-660500aA Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.0 aLargeScale Multiancestry Genomewide Study Accounting for Smoking c2018 Mar 01 a375-4000 v1023 aGenome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).
1 aSung, Yun, J1 aWinkler, Thomas, W1 aFuentes, Lisa, de Las1 aBentley, Amy, R1 aBrown, Michael, R1 aKraja, Aldi, T1 aSchwander, Karen1 aNtalla, Ioanna1 aGuo, Xiuqing1 aFranceschini, Nora1 aLu, Yingchang1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aMarten, Jonathan1 aMusani, Solomon, K1 aLi, Changwei1 aFeitosa, Mary, F1 aKilpeläinen, Tuomas, O1 aRichard, Melissa, A1 aNoordam, Raymond1 aAslibekyan, Stella1 aAschard, Hugues1 aBartz, Traci, M1 aDorajoo, Rajkumar1 aLiu, Yongmei1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, Vernon1 aTajuddin, Salman, M1 aTayo, Bamidele, O1 aWarren, Helen, R1 aZhao, Wei1 aZhou, Yanhua1 aMatoba, Nana1 aSofer, Tamar1 aAlver, Maris1 aAmini, Marzyeh1 aBoissel, Mathilde1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aGandin, Ilaria1 aGao, Chuan1 aGiulianini, Franco1 aGoel, Anuj1 aHarris, Sarah, E1 aHartwig, Fernando, Pires1 aHorimoto, Andrea, R V R1 aHsu, Fang-Chi1 aJackson, Anne, U1 aKähönen, Mika1 aKasturiratne, Anuradhani1 aKuhnel, Brigitte1 aLeander, Karin1 aLee, Wen-Jane1 aLin, Keng-Hung1 aLuan, Jian, 'an1 aMcKenzie, Colin, A1 aMeian, He1 aNelson, Christopher, P1 aRauramaa, Rainer1 aSchupf, Nicole1 aScott, Robert, A1 aSheu, Wayne, H H1 aStančáková, Alena1 aTakeuchi, Fumihiko1 avan der Most, Peter, J1 aVarga, Tibor, V1 aWang, Heming1 aWang, Yajuan1 aWare, Erin, B1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAfaq, Saima1 aAlfred, Tamuno1 aAmin, Najaf1 aArking, Dan1 aAung, Tin1 aBarr, Graham1 aBielak, Lawrence, F1 aBoerwinkle, Eric1 aBottinger, Erwin, P1 aBraund, Peter, S1 aBrody, Jennifer, A1 aBroeckel, Ulrich1 aCabrera, Claudia, P1 aCade, Brian1 aCaizheng, Yu1 aCampbell, Archie1 aCanouil, Mickaël1 aChakravarti, Aravinda1 aChauhan, Ganesh1 aChristensen, Kaare1 aCocca, Massimiliano1 aCollins, Francis, S1 aConnell, John, M1 ade Mutsert, Renée1 ade Silva, Janaka1 aDebette, Stephanie1 aDörr, Marcus1 aDuan, Qing1 aEaton, Charles, B1 aEhret, Georg1 aEvangelou, Evangelos1 aFaul, Jessica, D1 aFisher, Virginia, A1 aForouhi, Nita, G1 aFranco, Oscar, H1 aFriedlander, Yechiel1 aGao, He1 aGigante, Bruna1 aGraff, Misa1 aGu, Charles1 aGu, Dongfeng1 aGupta, Preeti1 aHagenaars, Saskia, P1 aHarris, Tamara, B1 aHe, Jiang1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHofman, Albert1 aHoward, Barbara, V1 aHunt, Steven1 aIrvin, Marguerite, R1 aJia, Yucheng1 aJoehanes, Roby1 aJustice, Anne, E1 aKatsuya, Tomohiro1 aKaufman, Joel1 aKerrison, Nicola, D1 aKhor, Chiea, Chuen1 aKoh, Woon-Puay1 aKoistinen, Heikki, A1 aKomulainen, Pirjo1 aKooperberg, Charles1 aKrieger, Jose, E1 aKubo, Michiaki1 aKuusisto, Johanna1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLewis, Cora, E1 aLi, Yize1 aLim, Sing, Hui1 aLin, Shiow1 aLiu, Ching-Ti1 aLiu, Jianjun1 aLiu, Jingmin1 aLiu, Kiang1 aLiu, Yeheng1 aLoh, Marie1 aLohman, Kurt, K1 aLong, Jirong1 aLouie, Tin1 aMägi, Reedik1 aMahajan, Anubha1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilani, Lili1 aMomozawa, Yukihide1 aMorris, Andrew, P1 aMosley, Thomas, H1 aMunson, Peter1 aMurray, Alison, D1 aNalls, Mike, A1 aNasri, Ubaydah1 aNorris, Jill, M1 aNorth, Kari1 aOgunniyi, Adesola1 aPadmanabhan, Sandosh1 aPalmas, Walter, R1 aPalmer, Nicholette, D1 aPankow, James, S1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPolasek, Ozren1 aRaitakari, Olli, T1 aRenstrom, Frida1 aRice, Treva, K1 aRidker, Paul, M1 aRobino, Antonietta1 aRobinson, Jennifer, G1 aRose, Lynda, M1 aRudan, Igor1 aSabanayagam, Charumathi1 aSalako, Babatunde, L1 aSandow, Kevin1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aScott, William, R1 aSeshadri, Sudha1 aSever, Peter1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aTang, Hua1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aUitterlinden, André, G1 aWaldenberger, Melanie1 aWang, Lihua1 aWang, Ya, X1 aBin Wei, Wen1 aWilliams, Christine1 aWilson, Gregory1 aWojczynski, Mary, K1 aYao, Jie1 aYuan, Jian-Min1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aChen, Yii-Der Ida1 ade Faire, Ulf1 aDeary, Ian, J1 aEsko, Tõnu1 aFarrall, Martin1 aForrester, Terrence1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aHorta, Bernardo, Lessa1 aHung, Yi-Jen1 aJonas, Jost, B1 aKato, Norihiro1 aKooner, Jaspal, S1 aLaakso, Markku1 aLehtimäki, Terho1 aLiang, Kae-Woei1 aMagnusson, Patrik, K E1 aNewman, Anne, B1 aOldehinkel, Albertine, J1 aPereira, Alexandre, C1 aRedline, Susan1 aRettig, Rainer1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aWu, Tangchun1 aZheng, Wei1 aKamatani, Yoichiro1 aLaurie, Cathy, C1 aBouchard, Claude1 aCooper, Richard, S1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKardia, Sharon, L R1 aKritchevsky, Stephen, B1 aLevy, Daniel1 aO'Connell, Jeff, R1 aPsaty, Bruce, M1 avan Dam, Rob, M1 aSims, Mario1 aArnett, Donna, K1 aMook-Kanamori, Dennis, O1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aFornage, Myriam1 aRotimi, Charles, N1 aProvince, Michael, A1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aLoos, Ruth, J F1 aReiner, Alex, P1 aRotter, Jerome, I1 aZhu, Xiaofeng1 aBierut, Laura, J1 aGauderman, James1 aCaulfield, Mark, J1 aElliott, Paul1 aRice, Kenneth1 aMunroe, Patricia, B1 aMorrison, Alanna, C1 aCupples, Adrienne, L1 aRao, Dabeeru, C1 aChasman, Daniel, I1 aCHARGE Neurology Working Group1 aCOGENT-Kidney Consortium1 aGIANT Consortium1 aLifeLines Cohort Study uhttps://chs-nhlbi.org/node/768611027nas a2203421 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2018 eng d a1932-620300aNovel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.0 aNovel genetic associations for blood pressure identified via gen c2018 ae01981660 v133 aHeavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
1 aFeitosa, Mary, F1 aKraja, Aldi, T1 aChasman, Daniel, I1 aSung, Yun, J1 aWinkler, Thomas, W1 aNtalla, Ioanna1 aGuo, Xiuqing1 aFranceschini, Nora1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aMarten, Jonathan1 aMusani, Solomon, K1 aLi, Changwei1 aBentley, Amy, R1 aBrown, Michael, R1 aSchwander, Karen1 aRichard, Melissa, A1 aNoordam, Raymond1 aAschard, Hugues1 aBartz, Traci, M1 aBielak, Lawrence, F1 aDorajoo, Rajkumar1 aFisher, Virginia1 aHartwig, Fernando, P1 aHorimoto, Andrea, R V R1 aLohman, Kurt, K1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, V1 aTajuddin, Salman, M1 aWojczynski, Mary, K1 aAlver, Maris1 aBoissel, Mathilde1 aCai, Qiuyin1 aCampbell, Archie1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aGao, Chuan1 aGoel, Anuj1 aHagemeijer, Yanick1 aHarris, Sarah, E1 aHe, Meian1 aHsu, Fang-Chi1 aJackson, Anne, U1 aKähönen, Mika1 aKasturiratne, Anuradhani1 aKomulainen, Pirjo1 aKuhnel, Brigitte1 aLaguzzi, Federica1 aLuan, Jian'an1 aMatoba, Nana1 aNolte, Ilja, M1 aPadmanabhan, Sandosh1 aRiaz, Muhammad1 aRueedi, Rico1 aRobino, Antonietta1 aSaid, Abdullah1 aScott, Robert, A1 aSofer, Tamar1 aStančáková, Alena1 aTakeuchi, Fumihiko1 aTayo, Bamidele, O1 avan der Most, Peter, J1 aVarga, Tibor, V1 aVitart, Veronique1 aWang, Yajuan1 aWare, Erin, B1 aWarren, Helen, R1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAfaq, Saima1 aAmin, Najaf1 aAmini, Marzyeh1 aArking, Dan, E1 aAung, Tin1 aBoerwinkle, Eric1 aBorecki, Ingrid1 aBroeckel, Ulrich1 aBrown, Morris1 aBrumat, Marco1 aBurke, Gregory, L1 aCanouil, Mickaël1 aChakravarti, Aravinda1 aCharumathi, Sabanayagam1 aChen, Yii-Der, Ida1 aConnell, John, M1 aCorrea, Adolfo1 aFuentes, Lisa, de Las1 ade Mutsert, Renée1 ade Silva, Janaka1 aDeng, Xuan1 aDing, Jingzhong1 aDuan, Qing1 aEaton, Charles, B1 aEhret, Georg1 aEppinga, Ruben, N1 aEvangelou, Evangelos1 aFaul, Jessica, D1 aFelix, Stephan, B1 aForouhi, Nita, G1 aForrester, Terrence1 aFranco, Oscar, H1 aFriedlander, Yechiel1 aGandin, Ilaria1 aGao, He1 aGhanbari, Mohsen1 aGigante, Bruna1 aGu, Charles1 aGu, Dongfeng1 aHagenaars, Saskia, P1 aHallmans, Göran1 aHarris, Tamara, B1 aHe, Jiang1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHoward, Barbara, V1 aIkram, Arfan, M1 aJohn, Ulrich1 aKatsuya, Tomohiro1 aKhor, Chiea, Chuen1 aKilpeläinen, Tuomas, O1 aKoh, Woon-Puay1 aKrieger, Jose, E1 aKritchevsky, Stephen, B1 aKubo, Michiaki1 aKuusisto, Johanna1 aLakka, Timo, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLewis, Cora, E1 aLi, Yize1 aLin, Shiow1 aLiu, Jianjun1 aLiu, Jingmin1 aLoh, Marie1 aLouie, Tin1 aMägi, Reedik1 aMcKenzie, Colin, A1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aMilani, Lili1 aMohlke, Karen, L1 aMomozawa, Yukihide1 aNalls, Mike, A1 aNelson, Christopher, P1 aSotoodehnia, Nona1 aNorris, Jill, M1 aO'Connell, Jeff, R1 aPalmer, Nicholette, D1 aPerls, Thomas1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPoulter, Neil1 aRaffel, Leslie, J1 aRaitakari, Olli, T1 aRoll, Kathryn1 aRose, Lynda, M1 aRosendaal, Frits, R1 aRotter, Jerome, I1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aSchupf, Nicole1 aScott, William, R1 aSever, Peter, S1 aShi, Yuan1 aSidney, Stephen1 aSims, Mario1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aStringham, Heather, M1 aTan, Nicholas, Y Q1 aTang, Hua1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aTurner, Stephen, T1 aUitterlinden, André, G1 aVollenweider, Peter1 aWaldenberger, Melanie1 aWang, Lihua1 aWang, Ya, Xing1 aBin Wei, Wen1 aWilliams, Christine1 aYao, Jie1 aYu, Caizheng1 aYuan, Jian-Min1 aZhao, Wei1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aDeary, Ian, J1 aEsko, Tõnu1 aFarrall, Martin1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aJonas, Jost, Bruno1 aKamatani, Yoichiro1 aKato, Norihiro1 aKooner, Jaspal, S1 aKutalik, Zoltán1 aLaakso, Markku1 aLaurie, Cathy, C1 aLeander, Karin1 aLehtimäki, Terho1 aStudy, Lifelines, Cohort1 aMagnusson, Patrik, K E1 aOldehinkel, Albertine, J1 aPenninx, Brenda, W J H1 aPolasek, Ozren1 aPorteous, David, J1 aRauramaa, Rainer1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aWu, Tangchun1 aZheng, Wei1 aBouchard, Claude1 aChristensen, Kaare1 aEvans, Michele, K1 aGudnason, Vilmundur1 aHorta, Bernardo, L1 aKardia, Sharon, L R1 aLiu, Yongmei1 aPereira, Alexandre, C1 aPsaty, Bruce, M1 aRidker, Paul, M1 avan Dam, Rob, M1 aGauderman, James1 aZhu, Xiaofeng1 aMook-Kanamori, Dennis, O1 aFornage, Myriam1 aRotimi, Charles, N1 aCupples, Adrienne, L1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aKooperberg, Charles1 aPalmas, Walter1 aRice, Kenneth1 aMorrison, Alanna, C1 aElliott, Paul1 aCaulfield, Mark, J1 aMunroe, Patricia, B1 aRao, Dabeeru, C1 aProvince, Michael, A1 aLevy, Daniel1 aInterAct Consortium uhttps://chs-nhlbi.org/node/779204864nas a2200733 4500008004100000022001400041245018700055210006900242260001300311300001200324490000700336520267100343100002303014700002203037700001603059700002403075700003203099700002003131700002003151700002203171700002403193700001703217700002103234700002803255700002903283700001603312700001903328700003103347700001903378700002203397700002403419700002503443700003203468700001703500700002003517700001503537700001903552700002003571700001803591700002003609700002003629700002003649700002403669700001903693700002003712700002003732700002203752700002803774700001903802700002403821700002103845700001903866700002503885700001903910700002503929700002103954700002303975700001103998700002204009700002104031700002204052700002004074856003604094 2018 eng d a1432-042800aSugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis.0 aSugarsweetened beverage intake associations with fasting glucose c2018 Feb a317-3300 v613 aAIMS/HYPOTHESIS: Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits.
METHODS: Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway.
RESULTS: In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10-3) and higher fasting insulin (0.030 ± 0.005 [log e pmol/l], p = 2.0 × 10-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030 ± 0.011 log e pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant.
CONCLUSIONS/INTERPRETATION: In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.
TRIAL REGISTRATION: Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study).
1 aMcKeown, Nicola, M1 aDashti, Hassan, S1 aMa, Jiantao1 aHaslam, Danielle, E1 ade Jong, Jessica, C Kiefte-1 aSmith, Caren, E1 aTanaka, Toshiko1 aGraff, Mariaelisa1 aLemaitre, Rozenn, N1 aRybin, Denis1 aSonestedt, Emily1 aFrazier-Wood, Alexis, C1 aMook-Kanamori, Dennis, O1 aLi, Yanping1 aWang, Carol, A1 aLeermakers, Elisabeth, T M1 aMikkilä, Vera1 aYoung, Kristin, L1 aMukamal, Kenneth, J1 aCupples, Adrienne, L1 aSchulz, Christina-Alexandra1 aChen, Tzu-An1 aLi-Gao, Ruifang1 aHuang, Tao1 aOddy, Wendy, H1 aRaitakari, Olli1 aRice, Kenneth1 aMeigs, James, B1 aEricson, Ulrika1 aSteffen, Lyn, M1 aRosendaal, Frits, R1 aHofman, Albert1 aKähönen, Mika1 aPsaty, Bruce, M1 aBrunkwall, Louise1 aUitterlinden, André, G1 aViikari, Jorma1 aSiscovick, David, S1 aSeppälä, Ilkka1 aNorth, Kari, E1 aMozaffarian, Dariush1 aDupuis, Josée1 aOrho-Melander, Marju1 aRich, Stephen, S1 ade Mutsert, Renée1 aQi, Lu1 aPennell, Craig, E1 aFranco, Oscar, H1 aLehtimäki, Terho1 aHerman, Mark, A uhttps://chs-nhlbi.org/node/757605481nas a2201285 4500008004100000022001400041245015800055210006900213260001600282520179200298100001902090700001702109700002102126700001702147700002902164700002102193700002402214700002002238700001302258700002002271700002102291700002102312700001302333700001502346700001902361700001602380700002202396700002102418700002302439700002302462700002502485700001902510700001902529700002102548700002502569700003002594700002302624700002702647700002002674700002302694700002202717700002202739700001802761700002802779700001902807700002402826700002202850700002102872700002002893700002402913700002002937700001902957700001602976700001802992700002003010700001803030700002203048700001903070700001803089700002003107700002003127700001903147700002003166700001803186700001903204700002003223700003103243700001903274700002003293700002003313700001903333700001903352700002203371700001903393700002003412700002103432700002003453700002103473700002203494700002103516700002503537700002003562700002403582700002503606700002303631700002203654700001703676700001903693700002303712700002003735700001903755700002003774700002403794700002603818700002003844700001903864700001503883700002103898700002403919700002403943700001903967700002003986700002804006700002004034700001704054700002004071700002304091710004504114856003604159 2018 eng d a1476-557800aWhole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation.0 aWhole exome sequencing study identifies novel rare and common Al c2018 Aug 143 aThe Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10), an immunoglobulin gene whose antibodies interact with β-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.
1 aBis, Joshua, C1 aJian, Xueqiu1 aKunkle, Brian, W1 aChen, Yuning1 aHamilton-Nelson, Kara, L1 aBush, William, S1 aSalerno, William, J1 aLancour, Daniel1 aMa, Yiyi1 aRenton, Alan, E1 aMarcora, Edoardo1 aFarrell, John, J1 aZhao, Yi1 aQu, Liming1 aAhmad, Shahzad1 aAmin, Najaf1 aAmouyel, Philippe1 aBeecham, Gary, W1 aBelow, Jennifer, E1 aCampion, Dominique1 aCharbonnier, Camille1 aChung, Jaeyoon1 aCrane, Paul, K1 aCruchaga, Carlos1 aCupples, Adrienne, L1 aDartigues, Jean-François1 aDebette, Stephanie1 aDeleuze, Jean-Francois1 aFulton, Lucinda1 aGabriel, Stacey, B1 aGenin, Emmanuelle1 aGibbs, Richard, A1 aGoate, Alison1 aGrenier-Boley, Benjamin1 aGupta, Namrata1 aHaines, Jonathan, L1 aHavulinna, Aki, S1 aHelisalmi, Seppo1 aHiltunen, Mikko1 aHowrigan, Daniel, P1 aIkram, Arfan, M1 aKaprio, Jaakko1 aKonrad, Jan1 aKuzma, Amanda1 aLander, Eric, S1 aLathrop, Mark1 aLehtimäki, Terho1 aLin, Honghuang1 aMattila, Kari1 aMayeux, Richard1 aMuzny, Donna, M1 aNasser, Waleed1 aNeale, Benjamin1 aNho, Kwangsik1 aNicolas, Gaël1 aPatel, Devanshi1 aPericak-Vance, Margaret, A1 aPerola, Markus1 aPsaty, Bruce, M1 aQuenez, Olivier1 aRajabli, Farid1 aRedon, Richard1 aReitz, Christiane1 aRemes, Anne, M1 aSalomaa, Veikko1 aSarnowski, Chloe1 aSchmidt, Helena1 aSchmidt, Michael1 aSchmidt, Reinhold1 aSoininen, Hilkka1 aThornton, Timothy, A1 aTosto, Giuseppe1 aTzourio, Christophe1 avan der Lee, Sven, J1 aDuijn, Cornelia, M1 aVardarajan, Badri1 aWang, Weixin1 aWijsman, Ellen1 aWilson, Richard, K1 aWitten, Daniela1 aWorley, Kim, C1 aZhang, Xiaoling1 aBellenguez, Céline1 aLambert, Jean-Charles1 aKurki, Mitja, I1 aPalotie, Aarno1 aDaly, Mark1 aBoerwinkle, Eric1 aLunetta, Kathryn, L1 aDeStefano, Anita, L1 aDupuis, Josée1 aMartin, Eden, R1 aSchellenberg, Gerard, D1 aSeshadri, Sudha1 aNaj, Adam, C1 aFornage, Myriam1 aFarrer, Lindsay, A1 aAlzheimer’s Disease Sequencing Project uhttps://chs-nhlbi.org/node/778517696nas a2205797 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2019 eng d a1546-171800aGenetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.0 aGenetic metaanalysis of diagnosed Alzheimers disease identifies c2019 Mar a414-4300 v513 aRisk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.
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Jennifer, A1 aDombroski, Beth, A1 aNaranjo, Maria, Candida De1 aDaniilidou, Makrina1 aEiriksdottir, Gudny1 aMukherjee, Shubhabrata1 aWallon, David1 aUphill, James1 aAspelund, Thor1 aCantwell, Laura, B1 aGarzia, Fabienne1 aGalimberti, Daniela1 aHofer, Edith1 aButkiewicz, Mariusz1 aFin, Bertrand1 aScarpini, Elio1 aSarnowski, Chloe1 aBush, Will, S1 aMeslage, Stéphane1 aKornhuber, Johannes1 aWhite, Charles, C1 aSong, Yuenjoo1 aBarber, Robert, C1 aEngelborghs, Sebastiaan1 aSordon, Sabrina1 aVoijnovic, Dina1 aAdams, Perrie, M1 aVandenberghe, Rik1 aMayhaus, Manuel1 aCupples, Adrienne, L1 aAlbert, Marilyn, S1 aDe Deyn, Peter, P1 aGu, Wei1 aHimali, Jayanadra, J1 aBeekly, Duane1 aSquassina, Alessio1 aHartmann, Annette, M1 aOrellana, Adelina1 aBlacker, Deborah1 aRodriguez-Rodriguez, Eloy1 aLovestone, Simon1 aGarcia, Melissa, E1 aDoody, Rachelle, S1 aMunoz-Fernadez, Carmen1 aSussams, Rebecca1 aLin, Honghuang1 aFairchild, Thomas, J1 aBenito, Yolanda, A1 aHolmes, Clive1 aKaramujić-Čomić, Hata1 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aRoyall, Donald, R1 aDufouil, Carole1 aMaletta, Raffaele, Giovanni1 ade Rojas, Itziar1 aSano, Mary1 aBrice, Alexis1 aCecchetti, Roberta1 aSt George-Hyslop, Peter1 aRitchie, Karen1 aTsolaki, Magda1 aTsuang, Debby, W1 aDubois, Bruno1 aCraig, David1 aWu, Chuang-Kuo1 aSoininen, Hilkka1 aAvramidou, Despoina1 aAlbin, Roger, L1 aFratiglioni, Laura1 aGermanou, Antonia1 aApostolova, Liana, G1 aKeller, Lina1 aKoutroumani, Maria1 aArnold, Steven, E1 aPanza, Francesco1 aGkatzima, Olymbia1 aAsthana, Sanjay1 aHannequin, Didier1 aWhitehead, Patrice1 aAtwood, Craig, S1 aCaffarra, Paolo1 aHampel, Harald1 aQuintela, Inés1 aCarracedo, Angel1 aLannfelt, Lars1 aRubinsztein, David, C1 aBarnes, Lisa, L1 aPasquier, Florence1 aFrölich, Lutz1 aBarral, Sandra1 aMcGuinness, Bernadette1 aBeach, Thomas, G1 aJohnston, Janet, A1 aBecker, James, T1 aPassmore, Peter1 aBigio, Eileen, H1 aSchott, Jonathan, M1 aBird, Thomas, D1 aWarren, Jason, D1 aBoeve, Bradley, F1 aLupton, Michelle, K1 aBowen, James, D1 aProitsi, Petra1 aBoxer, Adam1 aPowell, John, F1 aBurke, James, R1 aKauwe, John, S K1 aBurns, Jeffrey, M1 aMancuso, Michelangelo1 aBuxbaum, Joseph, D1 aBonuccelli, Ubaldo1 aCairns, Nigel, J1 aMcQuillin, Andrew1 aCao, Chuanhai1 aLivingston, Gill1 aCarlson, Chris, S1 aBass, Nicholas, J1 aCarlsson, Cynthia, M1 aHardy, John1 aCarney, Regina, M1 aBras, Jose1 aCarrasquillo, Minerva, M1 aGuerreiro, Rita1 aAllen, Mariet1 aChui, Helena, C1 aFisher, Elizabeth1 aMasullo, Carlo1 aCrocco, Elizabeth, A1 aDeCarli, Charles1 aBisceglio, Gina1 aDick, Malcolm1 aMa, Li1 aDuara, Ranjan1 aGraff-Radford, Neill, R1 aEvans, Denis, A1 aHodges, Angela1 aFaber, Kelley, M1 aScherer, Martin1 aFallon, Kenneth, B1 aRiemenschneider, Matthias1 aFardo, David, W1 aHeun, Reinhard1 aFarlow, Martin, R1 aKölsch, Heike1 aFerris, Steven1 aLeber, Markus1 aForoud, Tatiana, M1 aHeuser, Isabella1 aGalasko, Douglas, R1 aGiegling, Ina1 aGearing, Marla1 aHüll, Michael1 aGeschwind, Daniel, H1 aGilbert, John, R1 aMorris, John1 aGreen, Robert, C1 aMayo, 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Nick1 aLopez, Oscar, L1 aIngelsson, Martin1 aDeloukas, Panagiotis1 aCruchaga, Carlos1 aGraff, Caroline1 aGwilliam, Rhian1 aFornage, Myriam1 aGoate, Alison, M1 aSánchez-Juan, Pascual1 aKehoe, Patrick, G1 aAmin, Najaf1 aErtekin-Taner, Nilifur1 aBerr, Claudine1 aDebette, Stephanie1 aLove, Seth1 aLauner, Lenore, J1 aYounkin, Steven, G1 aDartigues, Jean-François1 aCorcoran, Chris1 aIkram, Arfan, M1 aDickson, Dennis, W1 aNicolas, Gaël1 aCampion, Dominique1 aTschanz, JoAnn1 aSchmidt, Helena1 aHakonarson, Hakon1 aClarimon, Jordi1 aMunger, Ron1 aSchmidt, Reinhold1 aFarrer, Lindsay, A1 aVan Broeckhoven, Christine1 aO'Donovan, Michael, C1 aDeStefano, Anita, L1 aJones, Lesley1 aHaines, Jonathan, L1 aDeleuze, Jean-Francois1 aOwen, Michael, J1 aGudnason, Vilmundur1 aMayeux, Richard1 aEscott-Price, Valentina1 aPsaty, Bruce, M1 aRamirez, Alfredo1 aSan Wang, Li-1 aRuiz, Agustin1 aDuijn, Cornelia, M1 aHolmans, Peter, A1 aSeshadri, Sudha1 aWilliams, Julie1 aAmouyel, Phillippe1 aSchellenberg, Gerard, D1 aLambert, Jean-Charles1 aPericak-Vance, Margaret, A1 aAlzheimer Disease Genetics Consortium (ADGC),1 aEuropean Alzheimer’s Disease Initiative (EADI),1 aCohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE),1 aGenetic and Environmental Risk in AD/Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease Consortium (GERAD/PERADES), uhttps://chs-nhlbi.org/node/797704013nas a2200685 4500008004100000022001400041245016200055210006900217260001600286300001200302490000800314520192200322100002102244700001702265700002302282700001502305700002202320700002002342700001702362700001602379700001702395700001802412700001202430700002302442700002202465700002302487700002502510700001702535700001802552700001902570700002602589700002002615700002402635700002202659700002102681700002002702700002202722700002102744700001902765700002402784700002002808700002302828700002502851700002502876700002502901700002702926700001902953700002402972700002102996700002203017700002103039700002203060700001903082700002003101710003403121710003603155710003603191710006403227856003603291 2019 eng d a1537-660500aImpact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.0 aImpact of Rare and Common Genetic Variants on Diabetes Diagnosis c2019 Oct 03 a706-7180 v1053 aHemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
1 aSarnowski, Chloe1 aLeong, Aaron1 aRaffield, Laura, M1 aWu, Peitao1 ade Vries, Paul, S1 aDiCorpo, Daniel1 aGuo, Xiuqing1 aXu, Huichun1 aLiu, Yongmei1 aZheng, Xiuwen1 aHu, Yao1 aBrody, Jennifer, A1 aGoodarzi, Mark, O1 aHidalgo, Bertha, A1 aHighland, Heather, M1 aJain, Deepti1 aLiu, Ching-Ti1 aNaik, Rakhi, P1 aO'Connell, Jeffrey, R1 aPerry, James, A1 aPorneala, Bianca, C1 aSelvin, Elizabeth1 aWessel, Jennifer1 aPsaty, Bruce, M1 aCurran, Joanne, E1 aPeralta, Juan, M1 aBlangero, John1 aKooperberg, Charles1 aMathias, Rasika1 aJohnson, Andrew, D1 aReiner, Alexander, P1 aMitchell, Braxton, D1 aCupples, Adrienne, L1 aVasan, Ramachandran, S1 aCorrea, Adolfo1 aMorrison, Alanna, C1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aRich, Stephen, S1 aManning, Alisa, K1 aDupuis, Josée1 aMeigs, James, B1 aTOPMed Diabetes Working Group1 aTOPMed Hematology Working Group1 aTOPMed Hemostasis Working Group1 aNational Heart, Lung, and Blood Institute TOPMed Consortium uhttps://chs-nhlbi.org/node/820510550nas a2203325 4500008004100000022001400041245010600055210006900161260001600230520134200246100002201588700002201610700002001632700001701652700002301669700001901692700002101711700001901732700001701751700002301768700002001791700001701811700002001828700002501848700002301873700001701896700002101913700002401934700002101958700002001979700002001999700002402019700001502043700002202058700002002080700002202100700002002122700002102142700002402163700002502187700002202212700001702234700002202251700002002273700001302293700001902306700001902325700001502344700001502359700002302374700002102397700002502418700001402443700002802457700001802485700002102503700002902524700002202553700002102575700002202596700001902618700001802637700002802655700001702683700001902700700001902719700001902738700001902757700002102776700001702797700002502814700002302839700002202862700002702884700002002911700001702931700001802948700001702966700001902983700001803002700001903020700001603039700001603055700001903071700001903090700001403109700002503123700002103148700002103169700002103190700002203211700002803233700002203261700002103283700001803304700002603322700002303348700002103371700002003392700002403412700001503436700002203451700002203473700002103495700002103516700002403537700002103561700002503582700002103607700002303628700001903651700002003670700001603690700002203706700002003728700002003748700001903768700002103787700002303808700002003831700002103851700001903872700002303891700002503914700002203939700002303961700002803984700001904012700002504031700001804056700002404074700002104098700002604119700001904145700002204164700001904186700002304205700002404228700002204252700002004274700002404294700001304318700002004331700001704351700001504368700001504383700001504398700001804413700002404431700002304455700002204478700002104500700002104521700001704542700002104559700002204580700002404602700001904626700002004645700002704665700002204692700002304714700002604737700001704763700002304780700002004803700002404823700001904847700001804866700002204884700002304906700002004929700001904949700002104968700002304989700002605012700001905038700001605057700002405073700002505097700002205122700001705144700001405161700002005175700001605195700002005211700002305231700002005254700001905274700002405293700001805317700002005335700001905355700002105374700002805395700002205423700002205445700002605467700001605493700001605509700001405525700001705539700002405556700002005580700002405600700001305624700001305637700001705650700001905667700001405686700002305700700002105723700002105744700002205765700002205787700001805809700001605827700002005843700002005863700002305883700002205906700002105928700002205949700002305971700002305994700001906017700002206036700001906058700001906077700002206096700002706118700002006145700002606165700002106191700002206212700001706234700001706251700001506268700002606283700001906309700002506328700001806353700001906371700003006390700001506420700001806435700001906453700002106472700002206493700002406515700001806539700001706557700002006574700002006594700002006614700002406634700001806658700002306676700002906699700002006728700002106748700001806769700002206787700002306809700001906832700002006851700001706871700002206888700002106910700002506931700002406956700001806980700002306998700002507021700002007046700002407066710002407090710007407114856003607188 2019 eng d a1476-625600aMulti-Ancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions.0 aMultiAncestry GenomeWide Association Study of Lipid Levels Incor c2019 Jan 293 aAn individual's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multi-ancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in Stage 1 (genome-wide discovery) and 66 studies in Stage 2 (focused follow-up), for a total of 394,584 individuals from five ancestry groups. Genetic main and interaction effects were jointly assessed by a 2 degrees of freedom (DF) test, and a 1 DF test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in Stage 1 and were evaluated in Stage 2, followed by combined analyses of Stage 1 and Stage 2. In the combined analysis of Stage 1 and Stage 2, 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2 DF tests, of which 18 were novel. No genome-wide significant associations were found testing the interaction effect alone. The novel loci included several genes (PCSK5, VEGFB, and A1CF) with a putative role in lipid metabolism based on existing evidence from cellular and experimental models.
1 ade Vries, Paul, S1 aBrown, Michael, R1 aBentley, Amy, R1 aSung, Yun, J1 aWinkler, Thomas, W1 aNtalla, Ioanna1 aSchwander, Karen1 aKraja, Aldi, T1 aGuo, Xiuqing1 aFranceschini, Nora1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aHuffman, Jennifer, E1 aMusani, Solomon, K1 aLi, Changwei1 aFeitosa, Mary, F1 aRichard, Melissa, A1 aNoordam, Raymond1 aAschard, Hugues1 aBartz, Traci, M1 aBielak, Lawrence, F1 aDeng, Xuan1 aDorajoo, Rajkumar1 aLohman, Kurt, K1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, V1 aTajuddin, Salman, M1 aEvangelou, Evangelos1 aGraff, Mariaelisa1 aAlver, Maris1 aBoissel, Mathilde1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aGandin, Ilaria1 aGao, Chuan1 aGoel, Anuj1 aHagemeijer, Yanick1 aHarris, Sarah, E1 aHartwig, Fernando, P1 aHe, Meian1 aHorimoto, Andrea, R V R1 aHsu, Fang-Chi1 aJackson, Anne, U1 aKasturiratne, Anuradhani1 aKomulainen, Pirjo1 aKuhnel, Brigitte1 aLaguzzi, Federica1 aLee, Joseph, H1 aLuan, Jian'an1 aLyytikäinen, Leo-Pekka1 aMatoba, Nana1 aNolte, Ilja, M1 aPietzner, Maik1 aRiaz, Muhammad1 aSaid, Abdullah1 aScott, Robert, A1 aSofer, Tamar1 aStančáková, Alena1 aTakeuchi, Fumihiko1 aTayo, Bamidele, O1 avan der Most, Peter, J1 aVarga, Tibor, V1 aWang, Yajuan1 aWare, Erin, B1 aWen, Wanqing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAfaq, Saima1 aAmin, Najaf1 aAmini, Marzyeh1 aArking, Dan, E1 aAung, Tin1 aBallantyne, Christie1 aBoerwinkle, Eric1 aBroeckel, Ulrich1 aCampbell, Archie1 aCanouil, Mickaël1 aCharumathi, Sabanayagam1 aChen, Yii-Der Ida1 aConnell, John, M1 ade Faire, Ulf1 aFuentes, Lisa, de Las1 ade Mutsert, Renée1 ade Silva, Janaka1 aDing, Jingzhong1 aDominiczak, Anna, F1 aDuan, Qing1 aEaton, Charles, B1 aEppinga, Ruben, N1 aFaul, Jessica, D1 aFisher, Virginia1 aForrester, Terrence1 aFranco, Oscar, H1 aFriedlander, Yechiel1 aGhanbari, Mohsen1 aGiulianini, Franco1 aGrabe, Hans, J1 aGrove, Megan, L1 aGu, Charles1 aHarris, Tamara, B1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHixson, James, E1 aHoward, Barbara, V1 aIkram, Arfan, M1 aJacobs, David, R1 aJohnson, Craig1 aJonas, Jost, Bruno1 aKammerer, Candace, M1 aKatsuya, Tomohiro1 aKhor, Chiea, Chuen1 aKilpeläinen, Tuomas, O1 aKoh, Woon-Puay1 aKoistinen, Heikki, A1 aKolcic, Ivana1 aKooperberg, Charles1 aKrieger, Jose, E1 aKritchevsky, Steve, B1 aKubo, Michiaki1 aKuusisto, Johanna1 aLakka, Timo, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLemaitre, Rozenn, N1 aLi, Yize1 aLiang, Jingjing1 aLiu, Jianjun1 aLiu, Kiang1 aLoh, Marie1 aLouie, Tin1 aMägi, Reedik1 aManichaikul, Ani, W1 aMcKenzie, Colin, A1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aMilani, Lili1 aMohlke, Karen, L1 aMosley, Thomas, H1 aMukamal, Kenneth, J1 aNalls, Mike, A1 aNauck, Matthias1 aNelson, Christopher, P1 aSotoodehnia, Nona1 aO'Connell, Jeff, R1 aPalmer, Nicholette, D1 aPazoki, Raha1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPolasek, Ozren1 aPoulter, Neil1 aRaffel, Leslie, J1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRice, Treva, K1 aRich, Stephen, S1 aRobino, Antonietta1 aRobinson, Jennifer, G1 aRose, Lynda, M1 aRudan, Igor1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aScott, William, R1 aSever, Peter1 aShi, Yuan1 aSidney, Stephen1 aSims, Mario1 aSmith, Blair, H1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aTan, Nicholas1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aUitterlinden, André, G1 avan Heemst, Diana1 aVuckovic, Dragana1 aWaldenberger, Melanie1 aWang, Lihua1 aWang, Yujie1 aWang, Zhe1 aBin Wei, Wen1 aWilliams, Christine1 aWilson, Gregory1 aWojczynski, Mary, K1 aYao, Jie1 aYu, Bing1 aYu, Caizheng1 aYuan, Jian-Min1 aZhao, Wei1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aDeary, Ian, J1 aEsko, Tõnu1 aFarrall, Martin1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aHorta, Bernardo, L1 aKamatani, Yoichiro1 aKato, Norihiro1 aKooner, Jaspal, S1 aLaakso, Markku1 aLeander, Karin1 aLehtimäki, Terho1 aMagnusson, Patrik, K E1 aPenninx, Brenda1 aPereira, Alexandre, C1 aRauramaa, Rainer1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWang, Ya, Xing1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aZheng, Wei1 aElliott, Paul1 aNorth, Kari, E1 aBouchard, Claude1 aEvans, Michele, K1 aGudnason, Vilmundur1 aLiu, Ching-Ti1 aLiu, Yongmei1 aPsaty, Bruce, M1 aRidker, Paul, M1 avan Dam, Rob, M1 aKardia, Sharon, L R1 aZhu, Xiaofeng1 aRotimi, Charles, N1 aMook-Kanamori, Dennis, O1 aFornage, Myriam1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aLiu, Jingmin1 aRotter, Jerome, I1 aGauderman, James1 aProvince, Michael, A1 aMunroe, Patricia, B1 aRice, Kenneth1 aChasman, Daniel, I1 aCupples, Adrienne, L1 aRao, Dabeeru, C1 aMorrison, Alanna, C1 aInterAct Consortium1 aLifelines Cohort, Groningen, The Netherlands (Lifelines Cohort Study) uhttps://chs-nhlbi.org/node/797011178nas a2203793 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2019 eng d a1546-171800aMulti-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids.0 aMultiancestry genomewide genesmoking interaction study of 387272 c2019 Apr a636-6480 v513 aThe concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
1 aBentley, Amy, R1 aSung, Yun, J1 aBrown, Michael, R1 aWinkler, Thomas, W1 aKraja, Aldi, T1 aNtalla, Ioanna1 aSchwander, Karen1 aChasman, Daniel, I1 aLim, Elise1 aDeng, Xuan1 aGuo, Xiuqing1 aLiu, Jingmin1 aLu, Yingchang1 aCheng, Ching-Yu1 aSim, Xueling1 aVojinovic, Dina1 aHuffman, Jennifer, E1 aMusani, Solomon, K1 aLi, Changwei1 aFeitosa, Mary, F1 aRichard, Melissa, A1 aNoordam, Raymond1 aBaker, Jenna1 aChen, Guanjie1 aAschard, Hugues1 aBartz, Traci, M1 aDing, Jingzhong1 aDorajoo, Rajkumar1 aManning, Alisa, K1 aRankinen, Tuomo1 aSmith, Albert, V1 aTajuddin, Salman, M1 aZhao, Wei1 aGraff, Mariaelisa1 aAlver, Maris1 aBoissel, Mathilde1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aEvangelou, Evangelos1 aGao, Chuan1 aGoel, Anuj1 aHagemeijer, Yanick1 aHarris, Sarah, E1 aHartwig, Fernando, P1 aHe, Meian1 aHorimoto, Andrea, R V R1 aHsu, Fang-Chi1 aHung, Yi-Jen1 aJackson, Anne, U1 aKasturiratne, Anuradhani1 aKomulainen, Pirjo1 aKuhnel, Brigitte1 aLeander, Karin1 aLin, Keng-Hung1 aLuan, Jian'an1 aLyytikäinen, Leo-Pekka1 aMatoba, Nana1 aNolte, Ilja, M1 aPietzner, Maik1 aPrins, Bram1 aRiaz, Muhammad1 aRobino, Antonietta1 aSaid, Abdullah1 aSchupf, Nicole1 aScott, Robert, A1 aSofer, Tamar1 aStančáková, Alena1 aTakeuchi, Fumihiko1 aTayo, Bamidele, O1 avan der Most, Peter, J1 aVarga, Tibor, V1 aWang, Tzung-Dau1 aWang, Yajuan1 aWare, Erin, B1 aWen, Wanqing1 aXiang, Yong-Bing1 aYanek, Lisa, R1 aZhang, Weihua1 aZhao, Jing Hua1 aAdeyemo, Adebowale1 aAfaq, Saima1 aAmin, Najaf1 aAmini, Marzyeh1 aArking, Dan, E1 aArzumanyan, Zorayr1 aAung, Tin1 aBallantyne, Christie1 aBarr, Graham1 aBielak, Lawrence, F1 aBoerwinkle, Eric1 aBottinger, Erwin, P1 aBroeckel, Ulrich1 aBrown, Morris1 aCade, Brian, E1 aCampbell, Archie1 aCanouil, Mickaël1 aCharumathi, Sabanayagam1 aChen, Yii-Der Ida1 aChristensen, Kaare1 aConcas, Maria, Pina1 aConnell, John, M1 aFuentes, Lisa, de Las1 ade Silva, Janaka1 ade Vries, Paul, S1 aDoumatey, Ayo1 aDuan, Qing1 aEaton, Charles, B1 aEppinga, Ruben, N1 aFaul, Jessica, D1 aFloyd, James, S1 aForouhi, Nita, G1 aForrester, Terrence1 aFriedlander, Yechiel1 aGandin, Ilaria1 aGao, He1 aGhanbari, Mohsen1 aGharib, Sina, A1 aGigante, Bruna1 aGiulianini, Franco1 aGrabe, Hans, J1 aGu, Charles1 aHarris, Tamara, B1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHirata, Makoto1 aHixson, James, E1 aIkram, Arfan, M1 aJia, Yucheng1 aJoehanes, Roby1 aJohnson, Craig1 aJonas, Jost, Bruno1 aJustice, Anne, E1 aKatsuya, Tomohiro1 aKhor, Chiea, Chuen1 aKilpeläinen, Tuomas, O1 aKoh, Woon-Puay1 aKolcic, Ivana1 aKooperberg, Charles1 aKrieger, Jose, E1 aKritchevsky, Stephen, B1 aKubo, Michiaki1 aKuusisto, Johanna1 aLakka, Timo, A1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLehne, Benjamin1 aLewis, Cora, E1 aLi, Yize1 aLiang, Jingjing1 aLin, Shiow1 aLiu, Ching-Ti1 aLiu, Jianjun1 aLiu, Kiang1 aLoh, Marie1 aLohman, Kurt, K1 aLouie, Tin1 aLuzzi, Anna1 aMägi, Reedik1 aMahajan, Anubha1 aManichaikul, Ani, W1 aMcKenzie, Colin, A1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aMilani, Lili1 aMohlke, Karen, L1 aMomozawa, Yukihide1 aMorris, Andrew, P1 aMurray, Alison, D1 aNalls, Mike, A1 aNauck, Matthias1 aNelson, Christopher, P1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPapanicolau, George, J1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPolasek, Ozren1 aPoulter, Neil1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRenstrom, Frida1 aRice, Treva, K1 aRich, Stephen, S1 aRobinson, Jennifer, G1 aRose, Lynda, M1 aRosendaal, Frits, R1 aRudan, Igor1 aSchmidt, Carsten, O1 aSchreiner, Pamela, J1 aScott, William, R1 aSever, Peter1 aShi, Yuan1 aSidney, Stephen1 aSims, Mario1 aSmith, Jennifer, A1 aSnieder, Harold1 aStarr, John, M1 aStrauch, Konstantin1 aStringham, Heather, M1 aTan, Nicholas, Y Q1 aTang, Hua1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aTham, Yih, Chung1 aTiemeier, Henning1 aTurner, Stephen, T1 aUitterlinden, André, G1 avan Heemst, Diana1 aWaldenberger, Melanie1 aWang, Heming1 aWang, Lan1 aWang, Lihua1 aBin Wei, Wen1 aWilliams, Christine, A1 aWilson, Gregory1 aWojczynski, Mary, K1 aYao, Jie1 aYoung, Kristin1 aYu, Caizheng1 aYuan, Jian-Min1 aZhou, Jie1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 aChambers, John, C1 aCooper, Richard, S1 ade Faire, Ulf1 aDeary, Ian, J1 aElliott, Paul1 aEsko, Tõnu1 aFarrall, Martin1 aFranks, Paul, W1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aHorta, Bernardo, L1 aJuang, Jyh-Ming, Jimmy1 aKamatani, Yoichiro1 aKammerer, Candace, M1 aKato, Norihiro1 aKooner, Jaspal, S1 aLaakso, Markku1 aLaurie, Cathy, C1 aLee, I-Te1 aLehtimäki, Terho1 aMagnusson, Patrik, K E1 aOldehinkel, Albertine, J1 aPenninx, Brenda, W J H1 aPereira, Alexandre, C1 aRauramaa, Rainer1 aRedline, Susan1 aSamani, Nilesh, J1 aScott, James1 aShu, Xiao-Ou1 aHarst, Pim1 aWagenknecht, Lynne, E1 aWang, Jun-Sing1 aWang, Ya, Xing1 aWareham, Nicholas, J1 aWatkins, Hugh1 aWeir, David, R1 aWickremasinghe, Ananda, R1 aWu, Tangchun1 aZeggini, Eleftheria1 aZheng, Wei1 aBouchard, Claude1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKardia, Sharon, L R1 aLiu, Yongmei1 aPsaty, Bruce, M1 aRidker, Paul, M1 avan Dam, Rob, M1 aMook-Kanamori, Dennis, O1 aFornage, Myriam1 aProvince, Michael, A1 aKelly, Tanika, N1 aFox, Ervin, R1 aHayward, Caroline1 aDuijn, Cornelia, M1 aTai, Shyong, E1 aWong, Tien, Yin1 aLoos, Ruth, J F1 aFranceschini, Nora1 aRotter, Jerome, I1 aZhu, Xiaofeng1 aBierut, Laura, J1 aGauderman, James1 aRice, Kenneth1 aMunroe, Patricia, B1 aMorrison, Alanna, C1 aRao, Dabeeru, C1 aRotimi, Charles, N1 aCupples, Adrienne, L1 aCOGENT-Kidney Consortium1 aEPIC-InterAct Consortium1 aUnderstanding Society Scientific Group1 aLifelines Cohort uhttps://chs-nhlbi.org/node/800506391nas a2201909 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2019 eng d a2041-172300aMulti-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.0 aMultiancestry sleepbySNP interaction analysis in 126926 individu c2019 Nov 12 a51210 v103 aBoth short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
1 aNoordam, Raymond1 aBos, Maxime, M1 aWang, Heming1 aWinkler, Thomas, W1 aBentley, Amy, R1 aKilpeläinen, Tuomas, O1 ade Vries, Paul, S1 aSung, Yun, Ju1 aSchwander, Karen1 aCade, Brian, E1 aManning, Alisa1 aAschard, Hugues1 aBrown, Michael, R1 aChen, Han1 aFranceschini, Nora1 aMusani, Solomon, K1 aRichard, Melissa1 aVojinovic, Dina1 aAslibekyan, Stella1 aBartz, Traci, M1 aFuentes, Lisa, de Las1 aFeitosa, Mary1 aHorimoto, Andrea, R1 aIlkov, Marjan1 aKho, Minjung1 aKraja, Aldi1 aLi, Changwei1 aLim, Elise1 aLiu, Yongmei1 aMook-Kanamori, Dennis, O1 aRankinen, Tuomo1 aTajuddin, Salman, M1 avan der Spek, Ashley1 aWang, Zhe1 aMarten, Jonathan1 aLaville, Vincent1 aAlver, Maris1 aEvangelou, Evangelos1 aGraff, Maria, E1 aHe, Meian1 aKuhnel, Brigitte1 aLyytikäinen, Leo-Pekka1 aMarques-Vidal, Pedro1 aNolte, Ilja, M1 aPalmer, Nicholette, D1 aRauramaa, Rainer1 aShu, Xiao-Ou1 aSnieder, Harold1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aAdolfo, Correa1 aBallantyne, Christie1 aBielak, Larry1 aBiermasz, Nienke, R1 aBoerwinkle, Eric1 aDimou, Niki1 aEiriksdottir, Gudny1 aGao, Chuan1 aGharib, Sina, A1 aGottlieb, Daniel, J1 aHaba-Rubio, José1 aHarris, Tamara, B1 aHeikkinen, Sami1 aHeinzer, Raphael1 aHixson, James, E1 aHomuth, Georg1 aIkram, Arfan, M1 aKomulainen, Pirjo1 aKrieger, Jose, E1 aLee, Jiwon1 aLiu, Jingmin1 aLohman, Kurt, K1 aLuik, Annemarie, I1 aMägi, Reedik1 aMartin, Lisa, W1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aNalls, Mike, A1 aO'Connell, Jeff1 aPeters, Annette1 aPeyser, Patricia1 aRaitakari, Olli, T1 aReiner, Alex, P1 aRensen, Patrick, C N1 aRice, Treva, K1 aRich, Stephen, S1 aRoenneberg, Till1 aRotter, Jerome, I1 aSchreiner, Pamela, J1 aShikany, James1 aSidney, Stephen, S1 aSims, Mario1 aSitlani, Colleen, M1 aSofer, Tamar1 aStrauch, Konstantin1 aSwertz, Morris, A1 aTaylor, Kent, D1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aVölzke, Henry1 aWaldenberger, Melanie1 aWallance, Robert, B1 aDijk, Ko Willems1 aYu, Caizheng1 aZonderman, Alan, B1 aBecker, Diane, M1 aElliott, Paul1 aEsko, Tõnu1 aGieger, Christian1 aGrabe, Hans, J1 aLakka, Timo, A1 aLehtimäki, Terho1 aNorth, Kari, E1 aPenninx, Brenda, W J H1 aVollenweider, Peter1 aWagenknecht, Lynne, E1 aWu, Tangchun1 aXiang, Yong-Bing1 aZheng, Wei1 aArnett, Donna, K1 aBouchard, Claude1 aEvans, Michele, K1 aGudnason, Vilmundur1 aKardia, Sharon1 aKelly, Tanika, N1 aKritchevsky, Stephen, B1 aLoos, Ruth, J F1 aPereira, Alexandre, C1 aProvince, Mike1 aPsaty, Bruce, M1 aRotimi, Charles1 aZhu, Xiaofeng1 aAmin, Najaf1 aCupples, Adrienne, L1 aFornage, Myriam1 aFox, Ervin, F1 aGuo, Xiuqing1 aGauderman, James1 aRice, Kenneth1 aKooperberg, Charles1 aMunroe, Patricia, B1 aLiu, Ching-Ti1 aMorrison, Alanna, C1 aRao, Dabeeru, C1 avan Heemst, Diana1 aRedline, Susan uhttps://chs-nhlbi.org/node/820210097nas a2203265 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2019 eng d a2041-172300aMulti-ancestry study of blood lipid levels identifies four loci interacting with physical activity.0 aMultiancestry study of blood lipid levels identifies four loci i c2019 01 22 a3760 v103 aMany genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.
10aAdolescent10aAdult10aAfrican Continental Ancestry Group10aAged10aAged, 80 and over10aAsian Continental Ancestry Group10aBrazil10aCalcium-Binding Proteins10aCholesterol10aCholesterol, HDL10aCholesterol, LDL10aEuropean Continental Ancestry Group10aExercise10aFemale10aGenetic Loci10aGenome-Wide Association Study10aGenotype10aHispanic Americans10aHumans10aLIM-Homeodomain Proteins10aLipid Metabolism10aLipids10aMale10aMembrane Proteins10aMicrotubule-Associated Proteins10aMiddle Aged10aMuscle Proteins10aNerve Tissue Proteins10aTranscription Factors10aTriglycerides10aYoung Adult1 aKilpeläinen, Tuomas, O1 aBentley, Amy, R1 aNoordam, Raymond1 aSung, Yun, Ju1 aSchwander, Karen1 aWinkler, Thomas, W1 aJakupović, Hermina1 aChasman, Daniel, I1 aManning, Alisa1 aNtalla, Ioanna1 aAschard, Hugues1 aBrown, Michael, R1 aFuentes, Lisa, de Las1 aFranceschini, Nora1 aGuo, Xiuqing1 aVojinovic, Dina1 aAslibekyan, Stella1 aFeitosa, Mary, F1 aKho, Minjung1 aMusani, Solomon, K1 aRichard, Melissa1 aWang, Heming1 aWang, Zhe1 aBartz, Traci, M1 aBielak, Lawrence, F1 aCampbell, Archie1 aDorajoo, Rajkumar1 aFisher, Virginia1 aHartwig, Fernando, P1 aHorimoto, Andrea, R V R1 aLi, Changwei1 aLohman, Kurt, K1 aMarten, Jonathan1 aSim, Xueling1 aSmith, Albert, V1 aTajuddin, Salman, M1 aAlver, Maris1 aAmini, Marzyeh1 aBoissel, Mathilde1 aChai, Jin, Fang1 aChen, Xu1 aDivers, Jasmin1 aEvangelou, Evangelos1 aGao, Chuan1 aGraff, Mariaelisa1 aHarris, Sarah, E1 aHe, Meian1 aHsu, Fang-Chi1 aJackson, Anne, U1 aZhao, Jing Hua1 aKraja, Aldi, T1 aKuhnel, Brigitte1 aLaguzzi, Federica1 aLyytikäinen, Leo-Pekka1 aNolte, Ilja, M1 aRauramaa, Rainer1 aRiaz, Muhammad1 aRobino, Antonietta1 aRueedi, Rico1 aStringham, Heather, M1 aTakeuchi, Fumihiko1 avan der Most, Peter, J1 aVarga, Tibor, V1 aVerweij, Niek1 aWare, Erin, B1 aWen, Wanqing1 aLi, Xiaoyin1 aYanek, Lisa, R1 aAmin, Najaf1 aArnett, Donna, K1 aBoerwinkle, Eric1 aBrumat, Marco1 aCade, Brian1 aCanouil, Mickaël1 aChen, Yii-Der Ida1 aConcas, Maria, Pina1 aConnell, John1 ade Mutsert, Renée1 ade Silva, Janaka1 ade Vries, Paul, S1 aDemirkan, Ayse1 aDing, Jingzhong1 aEaton, Charles, B1 aFaul, Jessica, D1 aFriedlander, Yechiel1 aGabriel, Kelley, P1 aGhanbari, Mohsen1 aGiulianini, Franco1 aGu, Chi, Charles1 aGu, Dongfeng1 aHarris, Tamara, B1 aHe, Jiang1 aHeikkinen, Sami1 aHeng, Chew-Kiat1 aHunt, Steven, C1 aIkram, Arfan, M1 aJonas, Jost, B1 aKoh, Woon-Puay1 aKomulainen, Pirjo1 aKrieger, Jose, E1 aKritchevsky, Stephen, B1 aKutalik, Zoltán1 aKuusisto, Johanna1 aLangefeld, Carl, D1 aLangenberg, Claudia1 aLauner, Lenore, J1 aLeander, Karin1 aLemaitre, Rozenn, N1 aLewis, Cora, E1 aLiang, Jingjing1 aLiu, Jianjun1 aMägi, Reedik1 aManichaikul, Ani1 aMeitinger, Thomas1 aMetspalu, Andres1 aMilaneschi, Yuri1 aMohlke, Karen, L1 aMosley, Thomas, H1 aMurray, Alison, D1 aNalls, Mike, A1 aNang, Ei-Ei, Khaing1 aNelson, Christopher, P1 aNona, Sotoodehnia1 aNorris, Jill, M1 aNwuba, Chiamaka, Vivian1 aO'Connell, Jeff1 aPalmer, Nicholette, D1 aPapanicolau, George, J1 aPazoki, Raha1 aPedersen, Nancy, L1 aPeters, Annette1 aPeyser, Patricia, A1 aPolasek, Ozren1 aPorteous, David, J1 aPoveda, Alaitz1 aRaitakari, Olli, T1 aRich, Stephen, S1 aRisch, Neil1 aRobinson, Jennifer, G1 aRose, Lynda, M1 aRudan, Igor1 aSchreiner, Pamela, J1 aScott, Robert, A1 aSidney, Stephen, S1 aSims, Mario1 aSmith, Jennifer, A1 aSnieder, Harold1 aSofer, Tamar1 aStarr, John, M1 aSternfeld, Barbara1 aStrauch, Konstantin1 aTang, Hua1 aTaylor, Kent, D1 aTsai, Michael, Y1 aTuomilehto, Jaakko1 aUitterlinden, André, G1 avan der Ende, Yldau1 avan Heemst, Diana1 aVoortman, Trudy1 aWaldenberger, Melanie1 aWennberg, Patrik1 aWilson, Gregory1 aXiang, Yong-Bing1 aYao, Jie1 aYu, Caizheng1 aYuan, Jian-Min1 aZhao, Wei1 aZonderman, Alan, B1 aBecker, Diane, M1 aBoehnke, Michael1 aBowden, Donald, W1 ade Faire, Ulf1 aDeary, Ian, J1 aElliott, Paul1 aEsko, Tõnu1 aFreedman, Barry, I1 aFroguel, Philippe1 aGasparini, Paolo1 aGieger, Christian1 aKato, Norihiro1 aLaakso, Markku1 aLakka, Timo, A1 aLehtimäki, Terho1 aMagnusson, Patrik, K E1 aOldehinkel, Albertine, J1 aPenninx, Brenda, W J H1 aSamani, Nilesh, J1 aShu, Xiao-Ou1 aHarst, Pim1 avan Vliet-Ostaptchouk, Jana, V1 aVollenweider, Peter1 aWagenknecht, Lynne, E1 aWang, Ya, X1 aWareham, Nicholas, J1 aWeir, David, R1 aWu, Tangchun1 aZheng, Wei1 aZhu, Xiaofeng1 aEvans, Michele, K1 aFranks, Paul, W1 aGudnason, Vilmundur1 aHayward, Caroline1 aHorta, Bernardo, L1 aKelly, Tanika, N1 aLiu, Yongmei1 aNorth, Kari, E1 aPereira, Alexandre, C1 aRidker, Paul, M1 aTai, Shyong, E1 avan Dam, Rob, M1 aFox, Ervin, R1 aKardia, Sharon, L R1 aLiu, Ching-Ti1 aMook-Kanamori, Dennis, O1 aProvince, Michael, A1 aRedline, Susan1 aDuijn, Cornelia, M1 aRotter, Jerome, I1 aKooperberg, Charles, B1 aGauderman, James1 aPsaty, Bruce, M1 aRice, Kenneth1 aMunroe, Patricia, B1 aFornage, Myriam1 aCupples, Adrienne, L1 aRotimi, Charles, N1 aMorrison, Alanna, C1 aRao, Dabeeru, C1 aLoos, Ruth, J F1 aLifeLines Cohort Study uhttps://chs-nhlbi.org/node/797602408nas a2200361 4500008004100000022001400041245012300055210006900178260001600247520131200263100002201575700002001597700001701617700002201634700001801656700001801674700002301692700002301715700002501738700001601763700001701779700002301796700002501819700002201844700002201866700002001888700002201908700002201930700001901952700001901971710002001990856003602010 2019 eng d a1473-115000aStatin-induced LDL cholesterol response and type 2 diabetes: a bidirectional two-sample Mendelian randomization study.0 aStatininduced LDL cholesterol response and type 2 diabetes a bid c2019 Dec 053 aIt remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, n = 40,914) and DIAGRAM (n = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (r = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.
1 aSmit, Roelof, A J1 aTrompet, Stella1 aLeong, Aaron1 aGoodarzi, Mark, O1 aPostmus, Iris1 aWarren, Helen1 aTheusch, Elizabeth1 aBarnes, Michael, R1 aArsenault, Benoit, J1 aLi, Xiaohui1 aFeng, QiPing1 aChasman, Daniel, I1 aCupples, Adrienne, L1 aHitman, Graham, A1 aKrauss, Ronald, M1 aPsaty, Bruce, M1 aRotter, Jerome, I1 ale Cessie, Saskia1 aStein, Michael1 aJukema, Wouter1 aGIST consortium uhttps://chs-nhlbi.org/node/829206570nas a2201753 4500008004100000022001400041245007100055210006900126260001200195300001200207490000800219520164100227100002301868700002501891700002601916700002201942700001701964700002401981700002002005700001902025700002602044700001902070700001602089700002002105700002902125700002702154700001602181700002202197700002002219700002002239700002502259700002402284700001902308700002002327700001902347700002002366700002402386700002002410700002602430700002702456700002502483700002402508700001402532700002202546700002302568700002102591700002302612700001902635700002302654700001702677700002302694700001802717700002102735700001902756700002302775700002502798700002202823700002402845700002402869700001902893700002702912700001902939700001702958700002202975700001902997700002103016700001903037700002203056700001903078700001903097700002003116700002203136700002203158700002503180700001903205700002103224700002303245700002103268700002303289700002303312700002203335700001903357700001803376700002203394700002103416700002203437700002103459700002103480700002003501700001903521700002003540700002203560700001803582700002203600700002003622700001703642700001703659700001603676700001503692700002703707700002303734700001703757700002403774700002103798700002003819700002103839700002403860700002503884700002403909700002303933700002503956700002303981700002104004700001904025700002004044700001904064700002804083700001804111700002104129700002104150700002304171700001804194700002004212700002304232700001804255700002404273700002104297700002504318700002104343700001704364700001704381700001804398700002104416700002204437700002104459700001704480700002204497700002004519700002304539700002304562700002504585700002404610700002204634700002304656700002204679700002304701710005604724856003604780 2020 eng d a1476-468700aInherited causes of clonal haematopoiesis in 97,691 whole genomes.0 aInherited causes of clonal haematopoiesis in 97691 whole genomes c2020 10 a763-7680 v5863 aAge is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.
1 aBick, Alexander, G1 aWeinstock, Joshua, S1 aNandakumar, Satish, K1 aFulco, Charles, P1 aBao, Erik, L1 aZekavat, Seyedeh, M1 aSzeto, Mindy, D1 aLiao, Xiaotian1 aLeventhal, Matthew, J1 aNasser, Joseph1 aChang, Kyle1 aLaurie, Cecelia1 aBurugula, Bala, Bharathi1 aGibson, Christopher, J1 aLin, Amy, E1 aTaub, Margaret, A1 aAguet, Francois1 aArdlie, Kristin1 aMitchell, Braxton, D1 aBarnes, Kathleen, C1 aMoscati, Arden1 aFornage, Myriam1 aRedline, Susan1 aPsaty, Bruce, M1 aSilverman, Edwin, K1 aWeiss, Scott, T1 aPalmer, Nicholette, D1 aVasan, Ramachandran, S1 aBurchard, Esteban, G1 aKardia, Sharon, L R1 aHe, Jiang1 aKaplan, Robert, C1 aSmith, Nicholas, L1 aArnett, Donna, K1 aSchwartz, David, A1 aCorrea, Adolfo1 ade Andrade, Mariza1 aGuo, Xiuqing1 aKonkle, Barbara, A1 aCuster, Brian1 aPeralta, Juan, M1 aGui, Hongsheng1 aMeyers, Deborah, A1 aMcGarvey, Stephen, T1 aChen, Ida Yii-Der1 aShoemaker, Benjamin1 aPeyser, Patricia, A1 aBroome, Jai, G1 aGogarten, Stephanie, M1 aWang, Fei, Fei1 aWong, Quenna1 aMontasser, May, E1 aDaya, Michelle1 aKenny, Eimear, E1 aNorth, Kari, E1 aLauner, Lenore, J1 aCade, Brian, E1 aBis, Joshua, C1 aCho, Michael, H1 aLasky-Su, Jessica1 aBowden, Donald, W1 aCupples, Adrienne, L1 aC Y Mak, Angel1 aBecker, Lewis, C1 aSmith, Jennifer, A1 aKelly, Tanika, N1 aAslibekyan, Stella1 aHeckbert, Susan, R1 aTiwari, Hemant, K1 aYang, Ivana, V1 aHeit, John, A1 aLubitz, Steven, A1 aJohnsen, Jill, M1 aCurran, Joanne, E1 aWenzel, Sally, E1 aWeeks, Daniel, E1 aRao, Dabeeru, C1 aDarbar, Dawood1 aMoon, Jee-Young1 aTracy, Russell, P1 aButh, Erin, J1 aRafaels, Nicholas1 aLoos, Ruth, J F1 aDurda, Peter1 aLiu, Yongmei1 aHou, Lifang1 aLee, Jiwon1 aKachroo, Priyadarshini1 aFreedman, Barry, I1 aLevy, Daniel1 aBielak, Lawrence, F1 aHixson, James, E1 aFloyd, James, S1 aWhitsel, Eric, A1 aEllinor, Patrick, T1 aIrvin, Marguerite, R1 aFingerlin, Tasha, E1 aRaffield, Laura, M1 aArmasu, Sebastian, M1 aWheeler, Marsha, M1 aSabino, Ester, C1 aBlangero, John1 aWilliams, Keoki1 aLevy, Bruce, D1 aSheu, Wayne, Huey-Herng1 aRoden, Dan, M1 aBoerwinkle, Eric1 aManson, JoAnn, E1 aMathias, Rasika, A1 aDesai, Pinkal1 aTaylor, Kent, D1 aJohnson, Andrew, D1 aAuer, Paul, L1 aKooperberg, Charles1 aLaurie, Cathy, C1 aBlackwell, Thomas, W1 aSmith, Albert, V1 aZhao, Hongyu1 aLange, Ethan1 aLange, Leslie1 aRich, Stephen, S1 aRotter, Jerome, I1 aWilson, James, G1 aScheet, Paul1 aKitzman, Jacob, O1 aLander, Eric, S1 aEngreitz, Jesse, M1 aEbert, Benjamin, L1 aReiner, Alexander, P1 aJaiswal, Siddhartha1 aAbecasis, Goncalo1 aSankaran, Vijay, G1 aKathiresan, Sekar1 aNatarajan, Pradeep1 aNHLBI Trans-Omics for Precision Medicine Consortium uhttps://chs-nhlbi.org/node/862103741nas a2200625 4500008004100000022001400041245009700055210006900152260001300221300001200234490000700246520194400253100001402197700001402211700002002225700002402245700002302269700002102292700002302313700001702336700001502353700002102368700002402389700001702413700001602430700002502446700002202471700002202493700001502515700002402530700002002554700002002574700002102594700002502615700002002640700002402660700002302684700002602707700001302733700001402746700002002760700002402780700002402804700001802828700002902846700002502875700002002900700001902920700002002939700002202959700002102981700002403002710005303026856003603079 2020 eng d a2574-830000aRole of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels.0 aRole of Rare and LowFrequency Variants in GeneAlcohol Interactio c2020 Aug ae0027720 v133 aBACKGROUND: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.
METHODS: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, ≤5%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.
RESULTS: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65×10 for the interaction test) and replicated at nominal significance level (=0.013) in .
CONCLUSIONS: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.
1 aWang, Zhe1 aChen, Han1 aBartz, Traci, M1 aBielak, Lawrence, F1 aChasman, Daniel, I1 aFeitosa, Mary, F1 aFranceschini, Nora1 aGuo, Xiuqing1 aLim, Elise1 aNoordam, Raymond1 aRichard, Melissa, A1 aWang, Heming1 aCade, Brian1 aCupples, Adrienne, L1 ade Vries, Paul, S1 aGiulanini, Franco1 aLee, Jiwon1 aLemaitre, Rozenn, N1 aMartin, Lisa, W1 aReiner, Alex, P1 aRich, Stephen, S1 aSchreiner, Pamela, J1 aSidney, Stephen1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 avan Dijk, Ko, Willems1 aYao, Jie1 aZhao, Wei1 aFornage, Myriam1 aKardia, Sharon, L R1 aKooperberg, Charles1 aLiu, Ching-Ti1 aMook-Kanamori, Dennis, O1 aProvince, Michael, A1 aPsaty, Bruce, M1 aRedline, Susan1 aRidker, Paul, M1 aRotter, Jerome, I1 aBoerwinkle, Eric1 aMorrison, Alanna, C1 aCHARGE Gene-Lifestyle Interactions Working Group uhttps://chs-nhlbi.org/node/840704776nas a2201261 4500008004100000022001400041245010300055210006900158260001500227300000900242490000700251520104900258653001001307653002201317653000901339653002201348653005001370653002901420653002401449653001101473653002201484653001701506653003801523653003401561653001101595653005001606653000901656653000901665653001601674653003601690653004101726653004301767653004001810653004601850653002801896100001701924700001601941700001801957700001801975700001501993700001502008700001702023700001902040700001702059700003002076700002902106700002202135700002302157700001302180700002102193700001902214700001902233700001502252700002002267700001902287700002302306700002002329700002502349700002002374700002002394700002402414700002002438700002702458700002102485700002002506700001702526700001902543700002002562700001702582700001702599700002202616700002302638700002002661700002502681700002802706700002202734700002402756700001702780700002602797700002002823700002302843700003102866700002502897700001902922700002002941700002102961700002402982700001903006700002003025700002103045700002403066700002503090700002403115700002203139700002003161700002103181700002503202700002303227700002603250700002503276700002403301700001703325700002003342700002103362710006503383710003003448856003603478 2020 eng d a2041-172300aWhole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants.0 aWhole genome sequence analysis of pulmonary function and COPD in c2020 10 14 a51820 v113 aChronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.
10aAdult10aAfrican Americans10aAged10aAged, 80 and over10aAlpha-Ketoglutarate-Dependent Dioxygenase FTO10aCalcium-Binding Proteins10aFeasibility Studies10aFemale10aFollow-Up Studies10aGenetic Loci10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aHumans10aIntracellular Signaling Peptides and Proteins10aLung10aMale10aMiddle Aged10aPolymorphism, Single Nucleotide10aProtein Inhibitors of Activated STAT10aPulmonary Disease, Chronic Obstructive10aRespiratory Physiological Phenomena10aSmall Ubiquitin-Related Modifier Proteins10aWhole Genome Sequencing1 aZhao, Xutong1 aQiao, Dandi1 aYang, Chaojie1 aKasela, Silva1 aKim, Wonji1 aMa, Yanlin1 aShrine, Nick1 aBatini, Chiara1 aSofer, Tamar1 aTaliun, Sarah, A Gagliano1 aSakornsakolpat, Phuwanat1 aBalte, Pallavi, P1 aProkopenko, Dmitry1 aYu, Bing1 aLange, Leslie, A1 aDupuis, Josée1 aCade, Brian, E1 aLee, Jiwon1 aGharib, Sina, A1 aDaya, Michelle1 aLaurie, Cecelia, A1 aRuczinski, Ingo1 aCupples, Adrienne, L1 aLoehr, Laura, R1 aBartz, Traci, M1 aMorrison, Alanna, C1 aPsaty, Bruce, M1 aVasan, Ramachandran, S1 aWilson, James, G1 aTaylor, Kent, D1 aDurda, Peter1 aJohnson, Craig1 aCornell, Elaine1 aGuo, Xiuqing1 aLiu, Yongmei1 aTracy, Russell, P1 aArdlie, Kristin, G1 aAguet, Francois1 aVanDenBerg, David, J1 aPapanicolaou, George, J1 aRotter, Jerome, I1 aBarnes, Kathleen, C1 aJain, Deepti1 aNickerson, Deborah, A1 aMuzny, Donna, M1 aMetcalf, Ginger, A1 aDoddapaneni, Harshavardhan1 aDugan-Perez, Shannon1 aGupta, Namrata1 aGabriel, Stacey1 aRich, Stephen, S1 aO'Connor, George, T1 aRedline, Susan1 aReed, Robert, M1 aLaurie, Cathy, C1 aDaviglus, Martha, L1 aPreudhomme, Liana, K1 aBurkart, Kristin, M1 aKaplan, Robert, C1 aWain, Louise, V1 aTobin, Martin, D1 aLondon, Stephanie, J1 aLappalainen, Tuuli1 aOelsner, Elizabeth, C1 aAbecasis, Goncalo, R1 aSilverman, Edwin, K1 aBarr, Graham1 aCho, Michael, H1 aManichaikul, Ani1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Lung Working Group uhttps://chs-nhlbi.org/node/863902650nas a2200589 4500008004100000022001400041245008000055210006900135260001600204490000600220520090300226100001301129700002401142700002201166700002301188700002401211700001401235700002701249700002501276700001301301700001701314700002501331700002401356700002101380700002101401700002001422700002401442700002301466700002001489700002501509700002101534700002001555700002401575700002301599700002701622700001701649700002801666700002001694700001401714700001901728700002201747700002001769700002101789700001701810700002201827700001901849700002601868700001901894700001601913710009501929856003602024 2021 eng d a2666-979X00aAssociation of mitochondrial DNA copy number with cardiometabolic diseases.0 aAssociation of mitochondrial DNA copy number with cardiometaboli c2021 Oct 130 v13 aMitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN ( = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN ( = 1.82 × 10) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity ( = 5.6 × 10), hypertension ( = 2.8 × 10), diabetes ( = 3.6 × 10), and hyperlipidemia ( = 6.3 × 10). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.
1 aLiu, Xue1 aLongchamps, Ryan, J1 aWiggins, Kerri, L1 aRaffield, Laura, M1 aBielak, Lawrence, F1 aZhao, Wei1 aPitsillides, Achilleas1 aBlackwell, Thomas, W1 aYao, Jie1 aGuo, Xiuqing1 aKurniansyah, Nuzulul1 aThyagarajan, Bharat1 aPankratz, Nathan1 aRich, Stephen, S1 aTaylor, Kent, D1 aPeyser, Patricia, A1 aHeckbert, Susan, R1 aSeshadri, Sudha1 aCupples, Adrienne, L1 aBoerwinkle, Eric1 aGrove, Megan, L1 aLarson, Nicholas, B1 aSmith, Jennifer, A1 aVasan, Ramachandran, S1 aSofer, Tamar1 aFitzpatrick, Annette, L1 aFornage, Myriam1 aDing, Jun1 aCorrea, Adolfo1 aAbecasis, Goncalo1 aPsaty, Bruce, M1 aWilson, James, G1 aLevy, Daniel1 aRotter, Jerome, I1 aBis, Joshua, C1 aSatizabal, Claudia, L1 aArking, Dan, E1 aLiu, Chunyu1 aTOPMed mtDNA Working Group in NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/899703306nas a2200565 4500008004100000022001400041245014400055210006900199260001600268490000600284520159100290100001701881700001501898700002501913700001701938700002301955700002701978700002402005700001702029700001202046700002402058700002202082700002702104700002502131700002402156700002002180700002002200700001402220700002602234700001502260700002402275700002002299700002002319700002202339700002002361700002102381700001702402700002102419700002402440700002102464700002302485700002102508700002002529700001902549700002302568700002102591700002702612710006502639856003602704 2021 eng d a2666-247700aBinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.0 aBinomiRare A robust test for association of a rare genetic varia c2021 Jul 080 v23 aWhole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.
1 aSofer, Tamar1 aLee, Jiwon1 aKurniansyah, Nuzulul1 aJain, Deepti1 aLaurie, Cecelia, A1 aGogarten, Stephanie, M1 aConomos, Matthew, P1 aHeavner, Ben1 aHu, Yao1 aKooperberg, Charles1 aHaessler, Jeffrey1 aVasan, Ramachandran, S1 aCupples, Adrienne, L1 aCoombes, Brandon, J1 aSeyerle, Amanda1 aGharib, Sina, A1 aChen, Han1 aO'Connell, Jeffrey, R1 aZhang, Man1 aGottlieb, Daniel, J1 aPsaty, Bruce, M1 aLongstreth, W T1 aRotter, Jerome, I1 aTaylor, Kent, D1 aRich, Stephen, S1 aGuo, Xiuqing1 aBoerwinkle, Eric1 aMorrison, Alanna, C1 aPankow, James, S1 aJohnson, Andrew, D1 aPankratz, Nathan1 aReiner, Alex, P1 aRedline, Susan1 aSmith, Nicholas, L1 aRice, Kenneth, M1 aSchifano, Elizabeth, D1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/883805153nas a2201369 4500008004100000022001400041245011700055210006900172260001500241300000900256490000700265520124400272100002301516700001901539700002101558700002701579700002001606700002201626700001901648700002601667700002601693700002001719700002001739700002301759700003001782700001901812700002301831700002901854700002801883700002401911700001901935700001901954700001201973700002401985700002102009700001702030700002502047700001902072700001802091700001502109700002402124700002002148700002002168700002202188700002002210700001702230700002602247700002602273700002102299700002402320700002302344700001802367700001902385700002102404700001902425700002102444700002202465700002102487700002102508700001902529700002102548700002202569700002002591700002102611700002002632700001902652700002202671700001802693700002202711700002402733700002002757700002302777700002002800700001802820700002202838700001402860700002002874700002002894700002202914700002402936700001802960700001702978700002402995700002103019700001803040700002403058700002003082700002203102700002303124700003003147700002503177700002503202700002603227700001903253700001903272700002103291700002003312700001403332700001903346700002503365700001703390700001903407700002103426700002203447700002703469700002203496700002503518700002203543700002403565700002103589700002003610700002003630700002003650710006503670710001203735856003603747 2021 eng d a2041-172300aChromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.0 aChromosome Xq23 is associated with lower atherogenic lipid conce c2021 04 12 a21820 v123 aAutosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
1 aNatarajan, Pradeep1 aPampana, Akhil1 aGraham, Sarah, E1 aRuotsalainen, Sanni, E1 aPerry, James, A1 ade Vries, Paul, S1 aBroome, Jai, G1 aPirruccello, James, P1 aHonigberg, Michael, C1 aAragam, Krishna1 aWolford, Brooke1 aBrody, Jennifer, A1 aAntonacci-Fulton, Lucinda1 aArden, Moscati1 aAslibekyan, Stella1 aAssimes, Themistocles, L1 aBallantyne, Christie, M1 aBielak, Lawrence, F1 aBis, Joshua, C1 aCade, Brian, E1 aDo, Ron1 aDoddapaneni, Harsha1 aEmery, Leslie, S1 aHung, Yi-Jen1 aIrvin, Marguerite, R1 aKhan, Alyna, T1 aLange, Leslie1 aLee, Jiwon1 aLemaitre, Rozenn, N1 aMartin, Lisa, W1 aMetcalf, Ginger1 aMontasser, May, E1 aMoon, Jee-Young1 aMuzny, Donna1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aStilp, Adrienne, M1 aTsai, Michael1 aWang, Fei, Fei1 aWeeks, Daniel, E1 aYanek, Lisa, R1 aWilson, James, G1 aAbecasis, Goncalo1 aArnett, Donna, K1 aBecker, Lewis, C1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aChang, Yi-Cheng1 aChen, Yii-der, I1 aChoi, Won, Jung1 aCorrea, Adolfo1 aCurran, Joanne, E1 aDaly, Mark, J1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aFornage, Myriam1 aFreedman, Barry, I1 aGabriel, Stacey1 aGermer, Soren1 aGibbs, Richard, A1 aHe, Jiang1 aHveem, Kristian1 aJarvik, Gail, P1 aKaplan, Robert, C1 aKardia, Sharon, L R1 aKenny, Eimear1 aKim, Ryan, W1 aKooperberg, Charles1 aLaurie, Cathy, C1 aLee, Seonwook1 aLloyd-Jones, Don, M1 aLoos, Ruth, J F1 aLubitz, Steven, A1 aMathias, Rasika, A1 aMartinez, Karine, A Viaud1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aNickerson, Deborah, A1 aNorth, Kari, E1 aPalotie, Aarno1 aPark, Cheol, Joo1 aPsaty, Bruce, M1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aSeo, Daekwan1 aSeo, Jeong-Sun1 aSmith, Albert, V1 aTracy, Russell, P1 aVasan, Ramachandran, S1 aKathiresan, Sekar1 aCupples, Adrienne, L1 aRotter, Jerome, I1 aMorrison, Alanna, C1 aRich, Stephen, S1 aRipatti, Samuli1 aWiller, Cristen1 aPeloso, Gina, M1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aFinnGen uhttps://chs-nhlbi.org/node/871109591nas a2202833 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2021 eng d a1537-660500aDiscovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry.0 aDiscovery and finemapping of height loci via highdensity imputat c2021 Apr 01 a564-5820 v1083 aAlthough many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
1 aGraff, Mariaelisa1 aJustice, Anne, E1 aYoung, Kristin, L1 aMarouli, Eirini1 aZhang, Xinruo1 aFine, Rebecca, S1 aLim, Elise1 aBuchanan, Victoria1 aRand, Kristin1 aFeitosa, Mary, F1 aWojczynski, Mary, K1 aYanek, Lisa, R1 aShao, Yaming1 aRohde, Rebecca1 aAdeyemo, Adebowale, A1 aAldrich, Melinda, C1 aAllison, Matthew, A1 aAmbrosone, Christine, B1 aAmbs, Stefan1 aAmos, Christopher1 aArnett, Donna, K1 aAtwood, Larry1 aBandera, Elisa, V1 aBartz, Traci1 aBecker, Diane, M1 aBerndt, Sonja, I1 aBernstein, Leslie1 aBielak, Lawrence, F1 aBlot, William, J1 aBottinger, Erwin, P1 aBowden, Donald, W1 aBradfield, Jonathan, P1 aBrody, Jennifer, A1 aBroeckel, Ulrich1 aBurke, Gregory1 aCade, Brian, E1 aCai, Qiuyin1 aCaporaso, Neil1 aCarlson, Chris1 aCarpten, John1 aCasey, Graham1 aChanock, Stephen, J1 aChen, Guanjie1 aChen, Minhui1 aChen, Yii-der, I1 aChen, Wei-Min1 aChesi, Alessandra1 aChiang, Charleston, W K1 aChu, Lisa1 aCoetzee, Gerry, A1 aConti, David, V1 aCooper, Richard, S1 aCushman, Mary1 aDemerath, Ellen1 aDeming, Sandra, L1 aDimitrov, Latchezar1 aDing, Jingzhong1 aDiver, Ryan1 aDuan, Qing1 aEvans, Michele, K1 aFalusi, Adeyinka, G1 aFaul, Jessica, D1 aFornage, Myriam1 aFox, Caroline1 aFreedman, Barry, I1 aGarcia, Melissa1 aGillanders, Elizabeth, M1 aGoodman, Phyllis1 aGottesman, Omri1 aGrant, Struan, F A1 aGuo, Xiuqing1 aHakonarson, Hakon1 aHaritunians, Talin1 aHarris, Tamara, B1 aHarris, Curtis, C1 aHenderson, Brian, E1 aHennis, Anselm1 aHernandez, Dena, G1 aHirschhorn, Joel, N1 aMcNeill, Lorna, Haughton1 aHoward, Timothy, D1 aHoward, Barbara1 aHsing, Ann, W1 aHsu, Yu-Han, H1 aHu, Jennifer, J1 aHuff, Chad, D1 aHuo, Dezheng1 aIngles, Sue, A1 aIrvin, Marguerite, R1 aJohn, Esther, M1 aJohnson, Karen, C1 aJordan, Joanne, M1 aKabagambe, Edmond, K1 aKang, Sun, J1 aKardia, Sharon, L1 aKeating, Brendan, J1 aKittles, Rick, A1 aKlein, Eric, A1 aKolb, Suzanne1 aKolonel, Laurence, N1 aKooperberg, Charles1 aKuller, Lewis1 aKutlar, Abdullah1 aLange, Leslie1 aLangefeld, Carl, D1 aLe Marchand, Loïc1 aLeonard, Hampton1 aLettre, Guillaume1 aLevin, Albert, M1 aLi, Yun1 aLi, Jin1 aLiu, Yongmei1 aLiu, Youfang1 aLiu, Simin1 aLohman, Kurt1 aLotay, Vaneet1 aLu, Yingchang1 aMaixner, William1 aManson, JoAnn, E1 aMcKnight, Barbara1 aMeng, Yan1 aMonda, Keri, L1 aMonroe, Kris1 aMoore, Jason, H1 aMosley, Thomas, H1 aMudgal, Poorva1 aMurphy, Adam, B1 aNadukuru, Raj1 aNalls, Mike, A1 aNathanson, Katherine, L1 aNayak, Uma1 aN'diaye, Amidou1 aNemesure, Barbara1 aNeslund-Dudas, Christine1 aNeuhouser, Marian, L1 aNyante, Sarah1 aOchs-Balcom, Heather1 aOgundiran, Temidayo, O1 aOgunniyi, Adesola1 aOjengbede, Oladosu1 aOkut, Hayrettin1 aOlopade, Olufunmilayo, I1 aOlshan, Andrew1 aPadhukasahasram, Badri1 aPalmer, Julie1 aPalmer, Cameron, D1 aPalmer, Nicholette, D1 aPapanicolaou, George1 aPatel, Sanjay, R1 aPettaway, Curtis, A1 aPeyser, Patricia, A1 aPress, Michael, F1 aRao, D, C1 aRasmussen-Torvik, Laura, J1 aRedline, Susan1 aReiner, Alex, P1 aRhie, Suhn, K1 aRodriguez-Gil, Jorge, L1 aRotimi, Charles, N1 aRotter, Jerome, I1 aRuiz-Narvaez, Edward, A1 aRybicki, Benjamin, A1 aSalako, Babatunde1 aSale, Michèle, M1 aSanderson, Maureen1 aSchadt, Eric1 aSchreiner, Pamela, J1 aSchurmann, Claudia1 aSchwartz, Ann, G1 aShriner, Daniel, A1 aSignorello, Lisa, B1 aSingleton, Andrew, B1 aSiscovick, David, S1 aSmith, Jennifer, A1 aSmith, Shad1 aSpeliotes, Elizabeth1 aSpitz, Margaret1 aStanford, Janet, L1 aStevens, Victoria, L1 aStram, Alex1 aStrom, Sara, S1 aSucheston, Lara1 aSun, Yan, V1 aTajuddin, Salman, M1 aTaylor, Herman1 aTaylor, Kira1 aTayo, Bamidele, O1 aThun, Michael, J1 aTucker, Margaret, A1 aVaidya, Dhananjay1 aVan Den Berg, David, J1 aVedantam, Sailaja1 aVitolins, Mara1 aWang, Zhaoming1 aWare, Erin, B1 aWassertheil-Smoller, Sylvia1 aWeir, David, R1 aWiencke, John, K1 aWilliams, Scott, M1 aWilliams, Keoki1 aWilson, James, G1 aWitte, John, S1 aWrensch, Margaret1 aWu, Xifeng1 aYao, Jie1 aZakai, Neil1 aZanetti, Krista1 aZemel, Babette, S1 aZhao, Wei1 aZhao, Jing Hua1 aZheng, Wei1 aZhi, Degui1 aZhou, Jie1 aZhu, Xiaofeng1 aZiegler, Regina, G1 aZmuda, Joe1 aZonderman, Alan, B1 aPsaty, Bruce, M1 aBorecki, Ingrid, B1 aCupples, Adrienne, L1 aLiu, Ching-Ti1 aHaiman, Christopher, A1 aLoos, Ruth1 aC Y Ng, Maggie1 aNorth, Kari, E uhttps://chs-nhlbi.org/node/870503417nas a2200493 4500008004100000022001400041245018000055210006900235260000900304300001300313490000700326520180900333100002102142700001402163700001902177700003202196700001802228700002502246700002202271700001902293700002102312700002502333700002002358700002702378700002502405700001702430700002002447700002402467700002102491700002502512700002402537700002602561700002002587700001802607700002102625700002702646700001802673700002102691700002402712700002402736710005302760710007402813856003602887 2021 eng d a1932-620300aIdentification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program.0 aIdentification of novel and rare variants associated with handgr c2021 ae02536110 v163 aHandgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.
1 aSarnowski, Chloe1 aChen, Han1 aBiggs, Mary, L1 aWassertheil-Smoller, Sylvia1 aBressler, Jan1 aIrvin, Marguerite, R1 aRyan, Kathleen, A1 aKarasik, David1 aArnett, Donna, K1 aCupples, Adrienne, L1 aFardo, David, W1 aGogarten, Stephanie, M1 aHeavner, Benjamin, D1 aJain, Deepti1 aKang, Hyun, Min1 aKooperberg, Charles1 aMainous, Arch, G1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aO'Connell, Jeffrey, R1 aPsaty, Bruce, M1 aRice, Kenneth1 aSmith, Albert, V1 aVasan, Ramachandran, S1 aWindham, Gwen1 aKiel, Douglas, P1 aMurabito, Joanne, M1 aLunetta, Kathryn, L1 aTOPMed Longevity and Healthy Aging Working Group1 afrom the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/883606260nas a2201741 4500008004100000022001400041245015100055210006900206260001600275490000600291520132000297100001601617700002101633700002301654700001801677700002301695700002101718700002001739700001701759700002801776700002001804700002001824700002001844700002401864700002201888700002601910700002501936700002801961700001701989700002202006700002102028700002102049700002102070700002102091700002802112700001902140700002102159700002702180700001602207700001802223700001802241700001702259700001902276700001902295700002102314700001502335700002102350700002102371700002602392700002202418700002502440700002502465700002602490700002302516700002202539700002502561700002202586700001802608700002102626700002202647700002002669700002502689700001602714700002202730700002802752700002002780700002002800700001802820700001902838700002302857700002202880700002202902700002102924700001702945700001702962700001702979700002302996700002003019700002203039700002103061700002303082700002203105700002003127700002403147700002603171700002203197700002003219700001803239700002603257700002403283700002903307700002503336700002203361700002203383700001703405700002003422700001603442700002303458700002203481700002403503700001903527700001703546700002803563700002303591700002603614700001803640700001803658700002003676700001503696700001303711700001803724700001403742700001803756700002303774700002103797700001803818700002203836700001903858700002203877700001903899700002903918700002703947700002003974700001803994700001904012700001504031700002204046700002104068700002404089700002304113700001804136700002904154700002404183700002604207700002004233700001604253700001804269700002404287700001704311700001804328700002204346700002404368700002304392700002004415700002004435710002704455856003604482 2021 eng d a2666-247700aMulti-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits.0 aMultiAncestry Genomewide Association Study Accounting for GenePs c2021 Jan 140 v23 aPsychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (), synaptic function and neurotransmission (), as well as genes previously implicated in neuropsychiatric or stress-related disorders (). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.
1 aSun, Daokun1 aRichard, Melissa1 aMusani, Solomon, K1 aSung, Yun, Ju1 aWinkler, Thomas, W1 aSchwander, Karen1 aChai, Jin, Fang1 aGuo, Xiuqing1 aKilpeläinen, Tuomas, O1 aVojinovic, Dina1 aAschard, Hugues1 aBartz, Traci, M1 aBielak, Lawrence, F1 aBrown, Michael, R1 aChitrala, Kumaraswamy1 aHartwig, Fernando, P1 aHorimoto, Andrea, R V R1 aLiu, Yongmei1 aManning, Alisa, K1 aNoordam, Raymond1 aSmith, Albert, V1 aHarris, Sarah, E1 aKuhnel, Brigitte1 aLyytikäinen, Leo-Pekka1 aNolte, Ilja, M1 aRauramaa, Rainer1 avan der Most, Peter, J1 aWang, Rujia1 aWare, Erin, B1 aWeiss, Stefan1 aWen, Wanqing1 aYanek, Lisa, R1 aArking, Dan, E1 aArnett, Donna, K1 aBarac, Ana1 aBoerwinkle, Eric1 aBroeckel, Ulrich1 aChakravarti, Aravinda1 aChen, Yii-Der Ida1 aCupples, Adrienne, L1 aDavigulus, Martha, L1 aFuentes, Lisa, de Las1 ade Mutsert, Renée1 ade Vries, Paul, S1 aDelaney, Joseph, A C1 aRoux, Ana, V Diez1 aDörr, Marcus1 aFaul, Jessica, D1 aFretts, Amanda, M1 aGallo, Linda, C1 aGrabe, Hans, Jörgen1 aGu, Charles1 aHarris, Tamara, B1 aHartman, Catharina, C A1 aHeikkinen, Sami1 aIkram, Arfan, M1 aIsasi, Carmen1 aJohnson, Craig1 aJonas, Jost, Bruno1 aKaplan, Robert, C1 aKomulainen, Pirjo1 aKrieger, Jose, E1 aLevy, Daniel1 aLiu, Jianjun1 aLohman, Kurt1 aLuik, Annemarie, I1 aMartin, Lisa, W1 aMeitinger, Thomas1 aMilaneschi, Yuri1 aO'Connell, Jeff, R1 aPalmas, Walter, R1 aPeters, Annette1 aPeyser, Patricia, A1 aPulkki-Råback, Laura1 aRaffel, Leslie, J1 aReiner, Alex, P1 aRice, Kenneth1 aRobinson, Jennifer, G1 aRosendaal, Frits, R1 aSchmidt, Carsten, Oliver1 aSchreiner, Pamela, J1 aSchwettmann, Lars1 aShikany, James, M1 aShu, Xiao-Ou1 aSidney, Stephen1 aSims, Mario1 aSmith, Jennifer, A1 aSotoodehnia, Nona1 aStrauch, Konstantin1 aTai, Shyong, E1 aTaylor, Kent1 aUitterlinden, André, G1 aDuijn, Cornelia, M1 aWaldenberger, Melanie1 aWee, Hwee-Lin1 aBin Wei, Wen-1 aWilson, Gregory1 aXuan, Deng1 aYao, Jie1 aZeng, Donglin1 aZhao, Wei1 aZhu, Xiaofeng1 aZonderman, Alan, B1 aBecker, Diane, M1 aDeary, Ian, J1 aGieger, Christian1 aLakka, Timo, A1 aLehtimäki, Terho1 aNorth, Kari, E1 aOldehinkel, Albertine, J1 aPenninx, Brenda, W J H1 aSnieder, Harold1 aWang, Ya-Xing1 aWeir, David, R1 aZheng, Wei1 aEvans, Michele, K1 aGauderman, James1 aGudnason, Vilmundur1 aHorta, Bernardo, L1 aLiu, Ching-Ti1 aMook-Kanamori, Dennis, O1 aMorrison, Alanna, C1 aPereira, Alexandre, C1 aPsaty, Bruce, M1 aAmin, Najaf1 aFox, Ervin, R1 aKooperberg, Charles1 aSim, Xueling1 aBierut, Laura1 aRotter, Jerome, I1 aKardia, Sharon, L R1 aFranceschini, Nora1 aRao, Dabeeru, C1 aFornage, Myriam1 aLifeLines Cohort Study uhttps://chs-nhlbi.org/node/900508483nas a2202413 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2021 eng d a1476-468700aSequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.0 aSequencing of 53831 diverse genomes from the NHLBI TOPMed Progra c2021 02 a290-2990 v5903 aThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
1 aTaliun, Daniel1 aHarris, Daniel, N1 aKessler, Michael, D1 aCarlson, Jedidiah1 aSzpiech, Zachary, A1 aTorres, Raul1 aTaliun, Sarah, A Gagliano1 aCorvelo, André1 aGogarten, Stephanie, M1 aKang, Hyun, Min1 aPitsillides, Achilleas, N1 aLeFaive, Jonathon1 aLee, Seung-Been1 aTian, Xiaowen1 aBrowning, Brian, L1 aDas, Sayantan1 aEmde, Anne-Katrin1 aClarke, Wayne, E1 aLoesch, Douglas, P1 aShetty, Amol, C1 aBlackwell, Thomas, W1 aSmith, Albert, V1 aWong, Quenna1 aLiu, Xiaoming1 aConomos, Matthew, P1 aBobo, Dean, M1 aAguet, Francois1 aAlbert, Christine1 aAlonso, Alvaro1 aArdlie, Kristin, G1 aArking, Dan, E1 aAslibekyan, Stella1 aAuer, Paul, L1 aBarnard, John1 aBarr, Graham1 aBarwick, Lucas1 aBecker, Lewis, C1 aBeer, Rebecca, L1 aBenjamin, Emelia, J1 aBielak, Lawrence, F1 aBlangero, John1 aBoehnke, Michael1 aBowden, Donald, W1 aBrody, Jennifer, A1 aBurchard, Esteban, G1 aCade, Brian, E1 aCasella, James, F1 aChalazan, Brandon1 aChasman, Daniel, I1 aChen, Yii-Der Ida1 aCho, Michael, H1 aChoi, Seung, Hoan1 aChung, Mina, K1 aClish, Clary, B1 aCorrea, Adolfo1 aCurran, Joanne, E1 aCuster, Brian1 aDarbar, Dawood1 aDaya, Michelle1 ade Andrade, Mariza1 aDeMeo, Dawn, L1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aEmery, Leslie, S1 aEng, Celeste1 aFatkin, Diane1 aFingerlin, Tasha1 aForer, Lukas1 aFornage, Myriam1 aFranceschini, Nora1 aFuchsberger, Christian1 aFullerton, Stephanie, M1 aGermer, Soren1 aGladwin, Mark, T1 aGottlieb, Daniel, J1 aGuo, Xiuqing1 aHall, Michael, E1 aHe, Jiang1 aHeard-Costa, Nancy, L1 aHeckbert, Susan, R1 aIrvin, Marguerite, R1 aJohnsen, Jill, M1 aJohnson, Andrew, D1 aKaplan, Robert1 aKardia, Sharon, L R1 aKelly, Tanika1 aKelly, Shannon1 aKenny, Eimear, E1 aKiel, Douglas, P1 aKlemmer, Robert1 aKonkle, Barbara, A1 aKooperberg, Charles1 aKöttgen, Anna1 aLange, Leslie, A1 aLasky-Su, Jessica1 aLevy, Daniel1 aLin, Xihong1 aLin, Keng-Han1 aLiu, Chunyu1 aLoos, Ruth, J F1 aGarman, Lori1 aGerszten, Robert1 aLubitz, Steven, A1 aLunetta, Kathryn, L1 aC Y Mak, Angel1 aManichaikul, Ani1 aManning, Alisa, K1 aMathias, Rasika, A1 aMcManus, David, D1 aMcGarvey, Stephen, T1 aMeigs, James, B1 aMeyers, Deborah, A1 aMikulla, Julie, L1 aMinear, Mollie, A1 aMitchell, Braxton, D1 aMohanty, Sanghamitra1 aMontasser, May, E1 aMontgomery, Courtney1 aMorrison, Alanna, C1 aMurabito, Joanne, M1 aNatale, Andrea1 aNatarajan, Pradeep1 aNelson, Sarah, C1 aNorth, Kari, E1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPankratz, Nathan1 aPeloso, Gina, M1 aPeyser, Patricia, A1 aPleiness, Jacob1 aPost, Wendy, S1 aPsaty, Bruce, M1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aRoden, Dan1 aRotter, Jerome, I1 aRuczinski, Ingo1 aSarnowski, Chloe1 aSchoenherr, Sebastian1 aSchwartz, David, A1 aSeo, Jeong-Sun1 aSeshadri, Sudha1 aSheehan, Vivien, A1 aSheu, Wayne, H1 aShoemaker, Benjamin1 aSmith, Nicholas, L1 aSmith, Jennifer, A1 aSotoodehnia, Nona1 aStilp, Adrienne, M1 aTang, Weihong1 aTaylor, Kent, D1 aTelen, Marilyn1 aThornton, Timothy, A1 aTracy, Russell, P1 aVan Den Berg, David, J1 aVasan, Ramachandran, S1 aViaud-Martinez, Karine, A1 aVrieze, Scott1 aWeeks, Daniel, E1 aWeir, Bruce, S1 aWeiss, Scott, T1 aWeng, Lu-Chen1 aWiller, Cristen, J1 aZhang, Yingze1 aZhao, Xutong1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBoerwinkle, Eric1 aGabriel, Stacey1 aGibbs, Richard1 aRice, Kenneth, M1 aRich, Stephen, S1 aSilverman, Edwin, K1 aQasba, Pankaj1 aGan, Weiniu1 aPapanicolaou, George, J1 aNickerson, Deborah, A1 aBrowning, Sharon, R1 aZody, Michael, C1 aZöllner, Sebastian1 aWilson, James, G1 aCupples, Adrienne, L1 aLaurie, Cathy, C1 aJaquish, Cashell, E1 aHernandez, Ryan, D1 aO'Connor, Timothy, D1 aAbecasis, Goncalo, R1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/866604296nas a2200973 4500008004100000022001400041245010700055210006900162260001600231520147300247100002301720700002101743700001901764700001801783700001901801700002301820700001901843700001701862700001901879700003001898700002601928700002801954700002801982700002102010700001702031700002202048700002302070700002202093700002202115700002102137700002402158700002302182700002002205700002402225700002002249700002102269700002302290700002402313700002402337700001902361700001902380700002002399700001902419700002502438700002302463700002402486700002002510700002302530700001602553700002202569700002002591700002002611700001702631700002202648700001802670700002402688700002402712700002302736700002402759700001902783700001502802700002302817700002502840700002502865700002202890700002402912700001902936700002602955700002602981700002103007700002103028700002203049700002303071700002003094700002703114700002103141700002003162700002103182700001903203700002003222700002303242700002103265856003603286 2021 eng d a1476-625600aA System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.0 aSystem for Phenotype Harmonization in the NHLBI TransOmics for P c2021 Apr 163 aGenotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.
1 aStilp, Adrienne, M1 aEmery, Leslie, S1 aBroome, Jai, G1 aButh, Erin, J1 aKhan, Alyna, T1 aLaurie, Cecelia, A1 aWang, Fei, Fei1 aWong, Quenna1 aChen, Dongquan1 aD'Augustine, Catherine, M1 aHeard-Costa, Nancy, L1 aHohensee, Chancellor, R1 aJohnson, William, Craig1 aJuarez, Lucia, D1 aLiu, Jingmin1 aMutalik, Karen, M1 aRaffield, Laura, M1 aWiggins, Kerri, L1 ade Vries, Paul, S1 aKelly, Tanika, N1 aKooperberg, Charles1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aPeyser, Patricia, A1 aReiner, Alex, P1 aArnett, Donna, K1 aAslibekyan, Stella1 aBarnes, Kathleen, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aCade, Brian, E1 aChen, Ming-Huei1 aCorrea, Adolfo1 aCupples, Adrienne, L1 ade Andrade, Mariza1 aEllinor, Patrick, T1 aFornage, Myriam1 aFranceschini, Nora1 aGan, Weiniu1 aGanesh, Santhi, K1 aGraffelman, Jan1 aGrove, Megan, L1 aGuo, Xiuqing1 aHawley, Nicola, L1 aHsu, Wan-Ling1 aJackson, Rebecca, D1 aJaquish, Cashell, E1 aJohnson, Andrew, D1 aKardia, Sharon, L R1 aKelly, Shannon1 aLee, Jiwon1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNorth, Kari, E1 aNouraie, Seyed, Mehdi1 aOelsner, Elizabeth, C1 aPankratz, Nathan1 aRich, Stephen, S1 aRotter, Jerome, I1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aWeeks, Daniel, E1 aWeiss, Scott, T1 aWilson, Carla, G1 aYanek, Lisa, R1 aPsaty, Bruce, M1 aHeckbert, Susan, R1 aLaurie, Cathy, C uhttps://chs-nhlbi.org/node/871304364nas a2200997 4500008004100000022001400041245016200055210006900217260001300286300001100299490000700310520151100317100002001828700002201848700002301870700002301893700002301916700002601939700002501965700002001990700002102010700002602031700001702057700002502074700002202099700001702121700001702138700002002155700002002175700002302195700001702218700002102235700001802256700001802274700001902292700001202311700001802323700001502341700002302356700002802379700001802407700002002425700002002445700002102465700002302486700002002509700002102529700002302550700001802573700002202591700002302613700002202636700001802658700002002676700002302696700002302719700001902742700002002761700001402781700002002795700002202815700002002837700002102857700002102878700001702899700002402916700001902940700002502959700001402984700002302998700002403021700002303045700002503068700002603093700002103119700002703140700002203167700001703189700002103206700001903227700002103246700001603267700002403283700002303307856003603330 2021 eng d a2352-396400aWhole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.0 aWhole genome sequence analyses of eGFR in 23732 people represent c2021 Jan a1031570 v633 aBACKGROUND: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.
METHODS: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.
FINDINGS: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.
INTERPRETATION: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.
1 aLin, Bridget, M1 aGrinde, Kelsey, E1 aBrody, Jennifer, A1 aBreeze, Charles, E1 aRaffield, Laura, M1 aMychaleckyj, Josyf, C1 aThornton, Timothy, A1 aPerry, James, A1 aBaier, Leslie, J1 aFuentes, Lisa, de Las1 aGuo, Xiuqing1 aHeavner, Benjamin, D1 aHanson, Robert, L1 aHung, Yi-Jen1 aQian, Huijun1 aHsiung, Chao, A1 aHwang, Shih-Jen1 aIrvin, Margaret, R1 aJain, Deepti1 aKelly, Tanika, N1 aKobes, Sayuko1 aLange, Leslie1 aLash, James, P1 aLi, Yun1 aLiu, Xiaoming1 aMi, Xuenan1 aMusani, Solomon, K1 aPapanicolaou, George, J1 aParsa, Afshin1 aReiner, Alex, P1 aSalimi, Shabnam1 aSheu, Wayne, H-H1 aShuldiner, Alan, R1 aTaylor, Kent, D1 aSmith, Albert, V1 aSmith, Jennifer, A1 aTin, Adrienne1 aVaidya, Dhananjay1 aWallace, Robert, B1 aYamamoto, Kenichi1 aSakaue, Saori1 aMatsuda, Koichi1 aKamatani, Yoichiro1 aMomozawa, Yukihide1 aYanek, Lisa, R1 aYoung, Betsi, A1 aZhao, Wei1 aOkada, Yukinori1 aAbecasis, Gonzalo1 aPsaty, Bruce, M1 aArnett, Donna, K1 aBoerwinkle, Eric1 aCai, Jianwen1 aDer Chen, Ida, Yii-1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aHe, Jiang1 aKardia, Sharon, Lr1 aKooperberg, Charles1 aMathias, Rasika, A1 aMitchell, Braxton, D1 aNickerson, Deborah, A1 aTurner, Steve, T1 aVasan, Ramachandran, S1 aRotter, Jerome, I1 aLevy, Daniel1 aKramer, Holly, J1 aKöttgen, Anna1 aRich, Stephen, S1 aLin, Dan-Yu1 aBrowning, Sharon, R1 aFranceschini, Nora uhttps://chs-nhlbi.org/node/866403828nas a2200625 4500008004100000022001400041245010800055210006900163260001500232300000800247490000700255520201900262100001902281700001502300700001702315700001702332700001502349700001402364700002002378700002402398700001702422700002402439700002002463700001602483700001302499700002102512700002202533700001802555700001902573700002102592700002002613700002202633700002202655700002002677700002002697700002302717700002502740700002402765700001902789700002502808700002202833700002602855700001902881700002002900700002202920700002102942700002202963700002702985700002103012700001803033700001903051710006503070710003103135856003603166 2021 eng d a1756-994X00aWhole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program.0 aWholegenome association analyses of sleepdisordered breathing ph c2021 08 26 a1360 v133 aBACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.
METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.
RESULTS: We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.
CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.
1 aCade, Brian, E1 aLee, Jiwon1 aSofer, Tamar1 aWang, Heming1 aZhang, Man1 aChen, Han1 aGharib, Sina, A1 aGottlieb, Daniel, J1 aGuo, Xiuqing1 aLane, Jacqueline, M1 aLiang, Jingjing1 aLin, Xihong1 aMei, Hao1 aPatel, Sanjay, R1 aPurcell, Shaun, M1 aSaxena, Richa1 aShah, Neomi, A1 aEvans, Daniel, S1 aHanis, Craig, L1 aHillman, David, R1 aMukherjee, Sutapa1 aPalmer, Lyle, J1 aStone, Katie, L1 aTranah, Gregory, J1 aAbecasis, Goncalo, R1 aBoerwinkle, Eric, A1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aKaplan, Robert, C1 aNickerson, Deborah, A1 aNorth, Kari, E1 aPsaty, Bruce, M1 aRotter, Jerome, I1 aRich, Stephen, S1 aTracy, Russell, P1 aVasan, Ramachandran, S1 aWilson, James, G1 aZhu, Xiaofeng1 aRedline, Susan1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Sleep Working Group uhttps://chs-nhlbi.org/node/892003404nas a2200757 4500008004100000022001400041245011100055210006900166260001300235300001200248490000700260520115000267100002601417700001701443700001701460700002501477700002401502700002201526700002701548700002501575700002001600700002401620700001801644700002501662700001501687700002301702700001901725700002701744700002101771700002401792700002101816700002201837700002601859700001901885700002301904700002401927700002801951700001901979700002001998700002002018700002302038700002402061700002702085700002302112700002002135700002102155700002202176700002302198700001902221700001702240700002002257700002302277700002302300700002502323700002402348700002102372700001902393700002102412700001902433700001602452700001502468700002302483710003902506710006502545856003602610 2022 eng d a1546-171800aAssessing the contribution of rare variants to complex trait heritability from whole-genome sequence data.0 aAssessing the contribution of rare variants to complex trait her c2022 Mar a263-2730 v543 aAnalyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.
1 aWainschtein, Pierrick1 aJain, Deepti1 aZheng, Zhili1 aCupples, Adrienne, L1 aShadyab, Aladdin, H1 aMcKnight, Barbara1 aShoemaker, Benjamin, M1 aMitchell, Braxton, D1 aPsaty, Bruce, M1 aKooperberg, Charles1 aLiu, Ching-Ti1 aAlbert, Christine, M1 aRoden, Dan1 aChasman, Daniel, I1 aDarbar, Dawood1 aLloyd-Jones, Donald, M1 aArnett, Donna, K1 aRegan, Elizabeth, A1 aBoerwinkle, Eric1 aRotter, Jerome, I1 aO'Connell, Jeffrey, R1 aYanek, Lisa, R1 ade Andrade, Mariza1 aAllison, Matthew, A1 aMcDonald, Merry-Lynn, N1 aChung, Mina, K1 aFornage, Myriam1 aChami, Nathalie1 aSmith, Nicholas, L1 aEllinor, Patrick, T1 aVasan, Ramachandran, S1 aMathias, Rasika, A1 aLoos, Ruth, J F1 aRich, Stephen, S1 aLubitz, Steven, A1 aHeckbert, Susan, R1 aRedline, Susan1 aGuo, Xiuqing1 aChen, Y, -D Ida1 aLaurie, Cecelia, A1 aHernandez, Ryan, D1 aMcGarvey, Stephen, T1 aGoddard, Michael, E1 aLaurie, Cathy, C1 aNorth, Kari, E1 aLange, Leslie, A1 aWeir, Bruce, S1 aYengo, Loic1 aYang, Jian1 aVisscher, Peter, M1 aTOPMed Anthropometry Working Group1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/904204304nas a2201045 4500008004100000022001400041245011400055210006900169260001300238300001400251490000700265520128500272653002201557653001101579653003401590653001101624653001401635653002801649100001401677700001401691700001701705700002201722700003201744700002401776700001801800700001501818700001401833700001401847700001601861700002101877700001801898700002401916700001901940700002501959700001901984700002102003700002202024700002302046700001902069700002402088700001902112700002502131700002202156700002202178700002802200700002302228700002302251700002502274700001702299700002102316700002402337700001902361700002102380700002002401700002102421700002202442700002002464700002302484700002002507700002502527700002202552700002402574700001702598700002602615700002602641700002402667700002002691700002302711700001902734700002502753700003402778700002102812700002102833700002302854700002002877700002202897700002702919700002102946700002102967700001902988700001403007700002203021700002303043700002303066700002003089700001603109710006503125710003203190856003603222 2022 eng d a1548-710500aA framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.0 aframework for detecting noncoding rarevariant associations of la c2022 Dec a1599-16110 v193 aLarge-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.
10aGenetic Variation10aGenome10aGenome-Wide Association Study10aHumans10aPhenotype10aWhole Genome Sequencing1 aLi, Zilin1 aLi, Xihao1 aZhou, Hufeng1 aGaynor, Sheila, M1 aSelvaraj, Margaret, Sunitha1 aArapoglou, Theodore1 aQuick, Corbin1 aLiu, Yaowu1 aChen, Han1 aSun, Ryan1 aDey, Rounak1 aArnett, Donna, K1 aAuer, Paul, L1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlackwell, Thomas, W1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aConomos, Matthew, P1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 ade Vries, Paul, S1 aDuggirala, Ravindranath1 aFranceschini, Nora1 aFreedman, Barry, I1 aGöring, Harald, H H1 aGuo, Xiuqing1 aKalyani, Rita, R1 aKooperberg, Charles1 aKral, Brian, G1 aLange, Leslie, A1 aLin, Bridget, M1 aManichaikul, Ani1 aManning, Alisa, K1 aMartin, Lisa, W1 aMathias, Rasika, A1 aMeigs, James, B1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNaseri, Take1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aRedline, Susan1 aReiner, Alexander, P1 aReupena, Muagututi'a, Sefuiva1 aRice, Kenneth, M1 aRich, Stephen, S1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aTaub, Margaret, A1 aVasan, Ramachandran, S1 aWeeks, Daniel, E1 aWilson, James, G1 aYanek, Lisa, R1 aZhao, Wei1 aRotter, Jerome, I1 aWiller, Cristen, J1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aLin, Xihong1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aTOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/925303962nas a2200733 4500008004100000022001400041245014300055210006900198260001600267520182100283100001602104700001602120700001502136700001802151700002202169700002102191700002002212700001802232700001602250700001302266700001902279700002302298700001702321700002002338700002602358700002002384700002302404700003102427700001902458700001902477700002502496700002502521700002002546700001702566700002202583700002102605700002002626700002002646700002402666700002702690700001902717700002102736700002402757700002102781700002202802700001702824700001902841700002002860700002002880700001902900700001902919700002502938700002302963700002602986700002403012700001703036700002503053700002403078700002003102700001903122700002103141710003003162856003603192 2022 eng d a1537-660500aPolygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program.0 aPolygenic transcriptome risk scores for COPD and lung function i c2022 Mar 313 aWhile polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV] and its ratio to forced vital capacity [FEV/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV and FEV/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk.
1 aHu, Xiaowei1 aQiao, Dandi1 aKim, Wonji1 aMoll, Matthew1 aBalte, Pallavi, P1 aLange, Leslie, A1 aBartz, Traci, M1 aKumar, Rajesh1 aLi, Xingnan1 aYu, Bing1 aCade, Brian, E1 aLaurie, Cecelia, A1 aSofer, Tamar1 aRuczinski, Ingo1 aNickerson, Deborah, A1 aMuzny, Donna, M1 aMetcalf, Ginger, A1 aDoddapaneni, Harshavardhan1 aGabriel, Stacy1 aGupta, Namrata1 aDugan-Perez, Shannon1 aCupples, Adrienne, L1 aLoehr, Laura, R1 aJain, Deepti1 aRotter, Jerome, I1 aWilson, James, G1 aPsaty, Bruce, M1 aFornage, Myriam1 aMorrison, Alanna, C1 aVasan, Ramachandran, S1 aWashko, George1 aRich, Stephen, S1 aO'Connor, George, T1 aBleecker, Eugene1 aKaplan, Robert, C1 aKalhan, Ravi1 aRedline, Susan1 aGharib, Sina, A1 aMeyers, Deborah1 aOrtega, Victor1 aDupuis, Josée1 aLondon, Stephanie, J1 aLappalainen, Tuuli1 aOelsner, Elizabeth, C1 aSilverman, Edwin, K1 aBarr, Graham1 aThornton, Timothy, A1 aWheeler, Heather, E1 aCho, Michael, H1 aIm, Hae, Kyung1 aManichaikul, Ani1 aTOPMed Lung Working Group uhttps://chs-nhlbi.org/node/903708881nas a2202605 4500008004100000022001400041245012200055210006900177260001500246300001000261490000800271520141300279653001201692653001801704653002501722653002601747653002301773653003001796653001001826653003801836653002201874653002501896653003401921653001101955653002101966653001101987653001001998653003402008653003102042653002402073653001402097653003602111100001802147700001902165700002102184700002002205700001802225700003202243700001702275700001702292700003102309700003002340700002102370700002102391700002302412700001602435700002802451700002902479700001802508700002102526700002402547700001902571700001902590700002102609700002502630700002102655700002202676700002102698700002302719700001902742700001902761700001902780700002702799700001702826700002002843700002102863700002002884700002002904700001902924700002902943700002402972700001902996700002503015700002203040700001703062700002203079700002303101700002403124700002803148700002203176700002403198700002103222700002003243700002003263700002303283700002103306700003103327700002803358700001803386700002203404700002203426700002103448700002303469700003903492700002203531700002103553700001803574700001903592700001703611700001903628700001503647700002003662700001903682700001403701700002603715700001703741700002103758700002503779700002603804700002003830700002003850700002403870700001803894700002103912700001903933700001703952700001703969700002003986700002504006700002404031700002204055700002004077700001904097700002104116700001504137700001704152700001804169700002104187700002404208700002104232700001704253700002004270700002204290700002304312700002004335700002804355700003604383700002304419700002504442700002004467700002004487700002204507700001904529700002604548700002304574700001504597700002104612700002204633700002004655700002904675700002404704700002004728700002104748700002204769700002604791700002504817700001904842700002304861700002604884700002104910700002104931700001904952700002104971700002404992700001905016700002005035700002005055700001405075700001405089700001905103700002505122700003105147700002105178700001905199700002405218700002305242700001705265700001905282700001705301700001605318700002105334700001805355700002305373700001905396700002205415700002005437700001905457700002005476700002105496700002105517700002205538700002305560700002405583700002105607700002005628700002705648700003005675700001905705700001605724700001805740700002105758700002105779700002105800700001905821700001905840700002205859700002105881700002205902700002105924700002205945700002305967700002305990700002306013700001906036700002006055710006106075710006506136710003806201856003606239 2022 eng d a1537-660500aRare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.0 aRare coding variants in 35 genes associate with circulating lipi c2022 01 06 a81-960 v1093 aLarge-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.
10aAlleles10aBlood Glucose10aCase-Control Studies10aComputational Biology10aDatabases, Genetic10aDiabetes Mellitus, Type 210aExome10aGenetic Predisposition to Disease10aGenetic Variation10aGenetics, Population10aGenome-Wide Association Study10aHumans10aLipid Metabolism10aLipids10aLiver10aMolecular Sequence Annotation10aMultifactorial Inheritance10aOpen Reading Frames10aPhenotype10aPolymorphism, Single Nucleotide1 aHindy, George1 aDornbos, Peter1 aChaffin, Mark, D1 aLiu, Dajiang, J1 aWang, Minxian1 aSelvaraj, Margaret, Sunitha1 aZhang, David1 aPark, Joseph1 aAguilar-Salinas, Carlos, A1 aAntonacci-Fulton, Lucinda1 aArdissino, Diego1 aArnett, Donna, K1 aAslibekyan, Stella1 aAtzmon, Gil1 aBallantyne, Christie, M1 aBarajas-Olmos, Francisco1 aBarzilai, Nir1 aBecker, Lewis, C1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBonnycastle, Lori, L1 aBottinger, Erwin1 aBowden, Donald, W1 aBown, Matthew, J1 aBrody, Jennifer, A1 aBroome, Jai, G1 aBurtt, Noel, P1 aCade, Brian, E1 aCenteno-Cruz, Federico1 aChan, Edmund1 aChang, Yi-Cheng1 aChen, Yii-der, I1 aCheng, Ching-Yu1 aChoi, Won, Jung1 aChowdhury, Raj1 aContreras-Cubas, Cecilia1 aCórdova, Emilio, J1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 aDanesh, John1 ade Vries, Paul, S1 aDeFronzo, Ralph, A1 aDoddapaneni, Harsha1 aDuggirala, Ravindranath1 aDutcher, Susan, K1 aEllinor, Patrick, T1 aEmery, Leslie, S1 aFlorez, Jose, C1 aFornage, Myriam1 aFreedman, Barry, I1 aFuster, Valentin1 aGaray-Sevilla, Ma, Eugenia1 aGarcía-Ortiz, Humberto1 aGermer, Soren1 aGibbs, Richard, A1 aGieger, Christian1 aGlaser, Benjamin1 aGonzalez, Clicerio1 aGonzalez-Villalpando, Maria, Elena1 aGraff, Mariaelisa1 aGraham, Sarah, E1 aGrarup, Niels1 aGroop, Leif, C1 aGuo, Xiuqing1 aGupta, Namrata1 aHan, Sohee1 aHanis, Craig, L1 aHansen, Torben1 aHe, Jiang1 aHeard-Costa, Nancy, L1 aHung, Yi-Jen1 aHwang, Mi, Yeong1 aIrvin, Marguerite, R1 aIslas-Andrade, Sergio1 aJarvik, Gail, P1 aKang, Hyun, Min1 aKardia, Sharon, L R1 aKelly, Tanika1 aKenny, Eimear, E1 aKhan, Alyna, T1 aKim, Bong-Jo1 aKim, Ryan, W1 aKim, Young, Jin1 aKoistinen, Heikki, A1 aKooperberg, Charles1 aKuusisto, Johanna1 aKwak, Soo, Heon1 aLaakso, Markku1 aLange, Leslie, A1 aLee, Jiwon1 aLee, Juyoung1 aLee, Seonwook1 aLehman, Donna, M1 aLemaitre, Rozenn, N1 aLinneberg, Allan1 aLiu, Jianjun1 aLoos, Ruth, J F1 aLubitz, Steven, A1 aLyssenko, Valeriya1 aMa, Ronald, C W1 aMartin, Lisa, Warsinger1 aMartínez-Hernández, Angélica1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMcPherson, Ruth1 aMeigs, James, B1 aMeitinger, Thomas1 aMelander, Olle1 aMendoza-Caamal, Elvia1 aMetcalf, Ginger, A1 aMi, Xuenan1 aMohlke, Karen, L1 aMontasser, May, E1 aMoon, Jee-Young1 aMoreno-Macias, Hortensia1 aMorrison, Alanna, C1 aMuzny, Donna, M1 aNelson, Sarah, C1 aNilsson, Peter, M1 aO'Connell, Jeffrey, R1 aOrho-Melander, Marju1 aOrozco, Lorena1 aPalmer, Colin, N A1 aPalmer, Nicholette, D1 aPark, Cheol, Joo1 aPark, Kyong, Soo1 aPedersen, Oluf1 aPeralta, Juan, M1 aPeyser, Patricia, A1 aPost, Wendy, S1 aPreuss, Michael1 aPsaty, Bruce, M1 aQi, Qibin1 aRao, D, C1 aRedline, Susan1 aReiner, Alexander, P1 aRevilla-Monsalve, Cristina1 aRich, Stephen, S1 aSamani, Nilesh1 aSchunkert, Heribert1 aSchurmann, Claudia1 aSeo, Daekwan1 aSeo, Jeong-Sun1 aSim, Xueling1 aSladek, Rob1 aSmall, Kerrin, S1 aSo, Wing, Yee1 aStilp, Adrienne, M1 aTai, Shyong, E1 aTam, Claudia, H T1 aTaylor, Kent, D1 aTeo, Yik, Ying1 aThameem, Farook1 aTomlinson, Brian1 aTsai, Michael, Y1 aTuomi, Tiinamaija1 aTuomilehto, Jaakko1 aTusié-Luna, Teresa1 aUdler, Miriam, S1 avan Dam, Rob, M1 aVasan, Ramachandran, S1 aMartinez, Karine, A Viaud1 aWang, Fei, Fei1 aWang, Xuzhi1 aWatkins, Hugh1 aWeeks, Daniel, E1 aWilson, James, G1 aWitte, Daniel, R1 aWong, Tien-Yin1 aYanek, Lisa, R1 aKathiresan, Sekar1 aRader, Daniel, J1 aRotter, Jerome, I1 aBoehnke, Michael1 aMcCarthy, Mark, I1 aWiller, Cristen, J1 aNatarajan, Pradeep1 aFlannick, Jason, A1 aKhera, Amit, V1 aPeloso, Gina, M1 aAMP-T2D-GENES, Myocardial Infarction Genetics Consortium1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium1 aNHLBI TOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/897504507nas a2201189 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2022 eng d a2397-337400aRare genetic variants explain missing heritability in smoking.0 aRare genetic variants explain missing heritability in smoking c2022 Aug 043 aCommon genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.
1 aJang, Seon-Kyeong1 aEvans, Luke1 aFialkowski, Allison1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBecker, Diane, M1 aBis, Joshua, C1 aBlangero, John1 aBleecker, Eugene, R1 aBoorgula, Meher, Preethi1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aJenkins, Brenda, W Campbell1 aCarson, April, P1 aChavan, Sameer1 aCupples, Adrienne, L1 aCuster, Brian1 aDamrauer, Scott, M1 aDavid, Sean, P1 ade Andrade, Mariza1 aDinardo, Carla, L1 aFingerlin, Tasha, E1 aFornage, Myriam1 aFreedman, Barry, I1 aGarrett, Melanie, E1 aGharib, Sina, A1 aGlahn, David, C1 aHaessler, Jeffrey1 aHeckbert, Susan, R1 aHokanson, John, E1 aHou, Lifang1 aHwang, Shih-Jen1 aHyman, Matthew, C1 aJudy, Renae1 aJustice, Anne, E1 aKaplan, Robert, C1 aKardia, Sharon, L R1 aKelly, Shannon1 aKim, Wonji1 aKooperberg, Charles1 aLevy, Daniel1 aLloyd-Jones, Donald, M1 aLoos, Ruth, J F1 aManichaikul, Ani, W1 aGladwin, Mark, T1 aMartin, Lisa, Warsinger1 aNouraie, Mehdi1 aMelander, Olle1 aMeyers, Deborah, A1 aMontgomery, Courtney, G1 aNorth, Kari, E1 aOelsner, Elizabeth, C1 aPalmer, Nicholette, D1 aPayton, Marinelle1 aPeljto, Anna, L1 aPeyser, Patricia, A1 aPreuss, Michael1 aPsaty, Bruce, M1 aQiao, Dandi1 aRader, Daniel, J1 aRafaels, Nicholas1 aRedline, Susan1 aReed, Robert, M1 aReiner, Alexander, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aSchwartz, David, A1 aShadyab, Aladdin, H1 aSilverman, Edwin, K1 aSmith, Nicholas, L1 aSmith, Gustav1 aSmith, Albert, V1 aSmith, Jennifer, A1 aTang, Weihong1 aTaylor, Kent, D1 aTelen, Marilyn, J1 aVasan, Ramachandran, S1 aGordeuk, Victor, R1 aWang, Zhe1 aWiggins, Kerri, L1 aYanek, Lisa, R1 aYang, Ivana, V1 aYoung, Kendra, A1 aYoung, Kristin, L1 aZhang, Yingze1 aLiu, Dajiang, J1 aKeller, Matthew, C1 aVrieze, Scott uhttps://chs-nhlbi.org/node/916805141nas a2201381 4500008004100000022001400041245014300055210006900198260001500267300000800282490000600290520117000296653003001466653001201496653001201508653001101520653001201531653005301543653002601596653003601622653002301658653002701681653001801708100002001726700002201746700002201768700002601790700002301816700002501839700001501864700002101879700002501900700001801925700002401943700002201967700002301989700002002012700001702032700002002049700002602069700001902095700002202114700001902136700001702155700001702172700003302189700002102222700001902243700001802262700002602280700002002306700002102326700002302347700002602370700002202396700002402418700002302442700002202465700002002487700002202507700002002529700002502549700002102574700002102595700001802616700001802634700002002652700002102672700002102693700001702714700002102731700003102752700002502783700003402808700002202842700002302864700002102887700001602908700001302924700001402937700002002951700001902971700002102990700001903011700002103030700001903051700002503070700002203095700002803117700001403145700002303159700002403182700001703206700002403223700001503247700002303262700002503285700002503310700002403335700002403359700002003383700001903403700002303422700002003445700002703465700003003492700002003522700002103542700001903563700002103582700002203603700001603625700001903641700002003660700002103680700002203701856003603723 2022 eng d a2399-364200aWhole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program.0 aWhole genome sequence association analysis of fasting glucose an c2022 07 28 a7560 v53 aThe genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.
10aDiabetes Mellitus, Type 210aFasting10aGlucose10aHumans10aInsulin10aNational Heart, Lung, and Blood Institute (U.S.)10aNerve Tissue Proteins10aPolymorphism, Single Nucleotide10aPrecision Medicine10aReceptors, Immunologic10aUnited States1 aDiCorpo, Daniel1 aGaynor, Sheila, M1 aRussell, Emily, M1 aWesterman, Kenneth, E1 aRaffield, Laura, M1 aMajarian, Timothy, D1 aWu, Peitao1 aSarnowski, Chloe1 aHighland, Heather, M1 aJackson, Anne1 aHasbani, Natalie, R1 ade Vries, Paul, S1 aBrody, Jennifer, A1 aHidalgo, Bertha1 aGuo, Xiuqing1 aPerry, James, A1 aO'Connell, Jeffrey, R1 aLent, Samantha1 aMontasser, May, E1 aCade, Brian, E1 aJain, Deepti1 aWang, Heming1 aAlbanus, Ricardo, D'Oliveira1 aVarshney, Arushi1 aYanek, Lisa, R1 aLange, Leslie1 aPalmer, Nicholette, D1 aAlmeida, Marcio1 aPeralta, Juan, M1 aAslibekyan, Stella1 aBaldridge, Abigail, S1 aBertoni, Alain, G1 aBielak, Lawrence, F1 aChen, Chung-Shiuan1 aChen, Yii-Der Ida1 aChoi, Won, Jung1 aGoodarzi, Mark, O1 aFloyd, James, S1 aIrvin, Marguerite, R1 aKalyani, Rita, R1 aKelly, Tanika, N1 aLee, Seonwook1 aLiu, Ching-Ti1 aLoesch, Douglas1 aManson, JoAnn, E1 aMinster, Ryan, L1 aNaseri, Take1 aPankow, James, S1 aRasmussen-Torvik, Laura, J1 aReiner, Alexander, P1 aReupena, Muagututi'a, Sefuiva1 aSelvin, Elizabeth1 aSmith, Jennifer, A1 aWeeks, Daniel, E1 aXu, Huichun1 aYao, Jie1 aZhao, Wei1 aParker, Stephen1 aAlonso, Alvaro1 aArnett, Donna, K1 aBlangero, John1 aBoerwinkle, Eric1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 aDuggirala, Ravindranath1 aHe, Jiang1 aHeckbert, Susan, R1 aKardia, Sharon, L R1 aKim, Ryan, W1 aKooperberg, Charles1 aLiu, Simin1 aMathias, Rasika, A1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMorrison, Alanna, C1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRedline, Susan1 aShuldiner, Alan, R1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aViaud-Martinez, Karine, A1 aFlorez, Jose, C1 aWilson, James, G1 aSladek, Robert1 aRich, Stephen, S1 aRotter, Jerome, I1 aLin, Xihong1 aDupuis, Josée1 aMeigs, James, B1 aWessel, Jennifer1 aManning, Alisa, K uhttps://chs-nhlbi.org/node/915803429nas a2200505 4500008004100000022001400041245009400055210006900149260001600218520189000234100002302124700002202147700002102169700002402190700002602214700002302240700002002263700002102283700001902304700001902323700002502342700001902367700002202386700001702408700002002425700002102445700001502466700002302481700002002504700002102524700002002545700001902565700002102584700001502605700002102620700002702641700002002668700002002688700002402708700002202732700001702754700002102771710009502792856003602887 2023 eng d a1935-554800aClonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk.0 aClonal Hematopoiesis of Indeterminate Potential CHIP and Inciden c2023 Sep 273 aOBJECTIVE: Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D.
RESEARCH DESIGN AND METHODS: CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis.
RESULTS: Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI = 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI = 1.05, 2.08) and ASXL1 (HR 1.76; CI = 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI = 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses.
CONCLUSIONS: CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.
1 aTobias, Deirdre, K1 aManning, Alisa, K1 aWessel, Jennifer1 aRaghavan, Sridharan1 aWesterman, Kenneth, E1 aBick, Alexander, G1 aDiCorpo, Daniel1 aWhitsel, Eric, A1 aCollins, Jason1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aDupuis, Josée1 aGoodarzi, Mark, O1 aGuo, Xiuqing1 aHoward, Barbara1 aLange, Leslie, A1 aLiu, Simin1 aRaffield, Laura, M1 aReiner, Alex, P1 aRich, Stephen, S1 aTaylor, Kent, D1 aTinker, Lesley1 aWilson, James, G1 aWu, Peitao1 aCarson, April, P1 aVasan, Ramachandran, S1 aFornage, Myriam1 aPsaty, Bruce, M1 aKooperberg, Charles1 aRotter, Jerome, I1 aMeigs, James1 aManson, JoAnn, E1 aTOPMed Diabetes Working Group; National Heart, Lung, and Blood Institute TOPMed Consortium uhttps://chs-nhlbi.org/node/950604607nas a2201201 4500008004100000022001400041245012100055210006900176260001300245300001400258490000700272520112800279100002001407700001901427700002101446700003201467700001601499700001501515700002301530700002801553700002001581700001701601700002401618700002201642700002201664700002101686700001801707700002801725700001701753700001701770700002001787700002001807700002801827700002001855700002101875700002801896700002401924700001701948700001901965700002101984700002002005700002302025700002102048700001702069700002402086700002402110700002202134700001902156700002302175700002202198700001902220700003302239700001802272700002202290700002302312700002002335700002002355700002602375700002102401700002902422700001702451700002102468700002102489700002002510700002902530700002102559700001602580700001802596700002502614700003002639700002202669700002702691700002002718700002302738700002402761700002402785700002202809700002002831700001802851700002102869700002002890700002102910700002202931700002302953700002302976700002002999700002003019700002803039700002303067700001903090700002303109700002003132700001903152700002203171700002803193700003003221700002403251700002403275700002103299700002803320700002103348856003603369 2023 eng d a1546-171800aMulti-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification.0 aMultiancestry genomewide study identifies effector genes and dru c2023 Oct a1651-16640 v553 aCoronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.
1 aKavousi, Maryam1 aBos, Maxime, M1 aBarnes, Hanna, J1 aCardenas, Christian, L Lino1 aWong, Doris1 aLu, Haojie1 aHodonsky, Chani, J1 aLandsmeer, Lennart, P L1 aTurner, Adam, W1 aKho, Minjung1 aHasbani, Natalie, R1 ade Vries, Paul, S1 aBowden, Donald, W1 aChopade, Sandesh1 aDeelen, Joris1 aBenavente, Ernest, Diez1 aGuo, Xiuqing1 aHofer, Edith1 aHwang, Shih-Jen1 aLutz, Sharon, M1 aLyytikäinen, Leo-Pekka1 aSlenders, Lotte1 aSmith, Albert, V1 aStanislawski, Maggie, A1 avan Setten, Jessica1 aWong, Quenna1 aYanek, Lisa, R1 aBecker, Diane, M1 aBeekman, Marian1 aBudoff, Matthew, J1 aFeitosa, Mary, F1 aFinan, Chris1 aHilliard, Austin, T1 aKardia, Sharon, L R1 aKovacic, Jason, C1 aKral, Brian, G1 aLangefeld, Carl, D1 aLauner, Lenore, J1 aMalik, Shaista1 aHoesein, Firdaus, A A Mohame1 aMokry, Michal1 aSchmidt, Reinhold1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aTerry, James, G1 avan der Grond, Jeroen1 avan Meurs, Joyce1 aVliegenthart, Rozemarijn1 aXu, Jianzhao1 aYoung, Kendra, A1 aZilhão, Nuno, R1 aZweiker, Robert1 aAssimes, Themistocles, L1 aBecker, Lewis, C1 aBos, Daniel1 aCarr, Jeffrey1 aCupples, Adrienne, L1 ade Kleijn, Dominique, P V1 ade Winther, Menno1 aRuijter, Hester, M den1 aFornage, Myriam1 aFreedman, Barry, I1 aGudnason, Vilmundur1 aHingorani, Aroon, D1 aHokanson, John, E1 aIkram, Arfan, M1 aIšgum, Ivana1 aJacobs, David, R1 aKähönen, Mika1 aLange, Leslie, A1 aLehtimäki, Terho1 aPasterkamp, Gerard1 aRaitakari, Olli, T1 aSchmidt, Helena1 aSlagboom, Eline1 aUitterlinden, André, G1 aVernooij, Meike, W1 aBis, Joshua, C1 aFranceschini, Nora1 aPsaty, Bruce, M1 aPost, Wendy, S1 aRotter, Jerome, I1 aBjörkegren, Johan, L M1 aO'Donnell, Christopher, J1 aBielak, Lawrence, F1 aPeyser, Patricia, A1 aMalhotra, Rajeev1 avan der Laan, Sander, W1 aMiller, Clint, L uhttps://chs-nhlbi.org/node/950103951nas a2200925 4500008004100000022001400041245013100055210006900186260001300255300001200268490000700280520122300287653002101510653003401531653001101565653001401576653002801590100001401618700001801632700001701650700002201667700001501689700001401704700003201718700001401750700001601764700002101780700002401801700001901825700001901844700002101863700002201884700002301906700001901929700001901948700002501967700002201992700002202014700002802036700002302064700002502087700001702112700002202129700002102151700002402172700001902196700002102215700002102236700002002257700002502277700002502302700002202327700002402349700001702373700002602390700002602416700002402442700002002466700002302486700001902509700002502528700003402553700002102587700002102608700002402629700002302653700002002676700002702696700002302723700002102746700001902767700001402786700002202800700002302822700002002845700001402865700001602879710009402895856003602989 2023 eng d a1546-171800aPowerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.0 aPowerful scalable and resourceefficient metaanalysis of rare var c2023 Jan a154-1640 v553 aMeta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.
10aExome Sequencing10aGenome-Wide Association Study10aLipids10aPhenotype10aWhole Genome Sequencing1 aLi, Xihao1 aQuick, Corbin1 aZhou, Hufeng1 aGaynor, Sheila, M1 aLiu, Yaowu1 aChen, Han1 aSelvaraj, Margaret, Sunitha1 aSun, Ryan1 aDey, Rounak1 aArnett, Donna, K1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBlangero, John1 aBoerwinkle, Eric1 aBowden, Donald, W1 aBrody, Jennifer, A1 aCade, Brian, E1 aCorrea, Adolfo1 aCupples, Adrienne, L1 aCurran, Joanne, E1 ade Vries, Paul, S1 aDuggirala, Ravindranath1 aFreedman, Barry, I1 aGöring, Harald, H H1 aGuo, Xiuqing1 aHaessler, Jeffrey1 aKalyani, Rita, R1 aKooperberg, Charles1 aKral, Brian, G1 aLange, Leslie, A1 aManichaikul, Ani1 aMartin, Lisa, W1 aMcGarvey, Stephen, T1 aMitchell, Braxton, D1 aMontasser, May, E1 aMorrison, Alanna, C1 aNaseri, Take1 aO'Connell, Jeffrey, R1 aPalmer, Nicholette, D1 aPeyser, Patricia, A1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aRedline, Susan1 aReiner, Alexander, P1 aReupena, Muagututi'a, Sefuiva1 aRice, Kenneth, M1 aRich, Stephen, S1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aTaylor, Kent, D1 aVasan, Ramachandran, S1 aWiller, Cristen, J1 aWilson, James, G1 aYanek, Lisa, R1 aZhao, Wei1 aRotter, Jerome, I1 aNatarajan, Pradeep1 aPeloso, Gina, M1 aLi, Zilin1 aLin, Xihong1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group uhttps://chs-nhlbi.org/node/923905493nas a2201573 4500008004100000245011200041210006900153260001600222520100600238100001801244700002301262700002201285700002501307700002001332700001501352700001401367700002001381700002101401700002201422700001401444700001401458700002401472700002101496700002401517700001901541700002901560700002201589700001901611700001801630700002801648700002001676700001901696700001901715700002101734700002401755700001901779700001701798700002801815700001701843700002201860700002301882700002401905700001701929700001801946700002501964700002001989700002102009700001602030700002002046700001602066700001302082700001802095700002402113700001702137700002102154700002402175700002102199700002002220700002002240700001702260700002202277700002802299700002302327700002402350700001702374700002302391700003002414700002602444700002102470700002002491700001902511700002302530700001402553700002402567700002402591700001802615700002802633700002402661700002302685700002202708700002702730700001702757700002102774700002102795700002202816700002202838700002302860700001902883700002302902700001402925700002402939700002102963700002802984700002403012700001903036700002103055700002503076700002103101700002303122700002203145700002203167700002003189700002303209700001403232700002303246700001603269700002503285700002403310700002103334700002503355700001903380700002003399700002303419700002503442700002103467700002203488700002403510700002303534700002003557700002203577700002003599700001803619700002503637700001603662700001603678700002503694700002103719700001803740700002003758700001903778700002103797710006503818856003603883 2023 eng d00aWHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES NOVEL AFRICAN ANCESTRY-SPECIFIC RISK ALLELE.0 aWHOLE GENOME SEQUENCING ANALYSIS OF BODY MASS INDEX IDENTIFIES N c2023 Aug 223 aObesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals ( < 5 × 10 ). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the and loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.
1 aZhang, Xinruo1 aBrody, Jennifer, A1 aGraff, Mariaelisa1 aHighland, Heather, M1 aChami, Nathalie1 aXu, Hanfei1 aWang, Zhe1 aFerrier, Kendra1 aChittoor, Geetha1 aJosyula, Navya, S1 aLi, Xihao1 aLi, Zilin1 aAllison, Matthew, A1 aBecker, Diane, M1 aBielak, Lawrence, F1 aBis, Joshua, C1 aBoorgula, Meher, Preethi1 aBowden, Donald, W1 aBroome, Jai, G1 aButh, Erin, J1 aCarlson, Christopher, S1 aChang, Kyong-Mi1 aChavan, Sameer1 aChiu, Yen-Feng1 aChuang, Lee-Ming1 aConomos, Matthew, P1 aDeMeo, Dawn, L1 aDu, Margaret1 aDuggirala, Ravindranath1 aEng, Celeste1 aFohner, Alison, E1 aFreedman, Barry, I1 aGarrett, Melanie, E1 aGuo, Xiuqing1 aHaiman, Chris1 aHeavner, Benjamin, D1 aHidalgo, Bertha1 aHixson, James, E1 aHo, Yuk-Lam1 aHobbs, Brian, D1 aHu, Donglei1 aHui, Qin1 aHwu, Chii-Min1 aJackson, Rebecca, D1 aJain, Deepti1 aKalyani, Rita, R1 aKardia, Sharon, L R1 aKelly, Tanika, N1 aLange, Ethan, M1 aLeNoir, Michael1 aLi, Changwei1 aLe Marchand, Loic1 aMcDonald, Merry-Lynn, N1 aMcHugh, Caitlin, P1 aMorrison, Alanna, C1 aNaseri, Take1 aO'Connell, Jeffrey1 aO'Donnell, Christopher, J1 aPalmer, Nicholette, D1 aPankow, James, S1 aPerry, James, A1 aPeters, Ulrike1 aPreuss, Michael, H1 aRao, D, C1 aRegan, Elizabeth, A1 aReupena, Sefuiva, M1 aRoden, Dan, M1 aRodriguez-Santana, Jose1 aSitlani, Colleen, M1 aSmith, Jennifer, A1 aTiwari, Hemant, K1 aVasan, Ramachandran, S1 aWang, Zeyuan1 aWeeks, Daniel, E1 aWessel, Jennifer1 aWiggins, Kerri, L1 aWilkens, Lynne, R1 aWilson, Peter, W F1 aYanek, Lisa, R1 aYoneda, Zachary, T1 aZhao, Wei1 aZöllner, Sebastian1 aArnett, Donna, K1 aAshley-Koch, Allison, E1 aBarnes, Kathleen, C1 aBlangero, John1 aBoerwinkle, Eric1 aBurchard, Esteban, G1 aCarson, April, P1 aChasman, Daniel, I1 aChen, Yii-Der Ida1 aCurran, Joanne, E1 aFornage, Myriam1 aGordeuk, Victor, R1 aHe, Jiang1 aHeckbert, Susan, R1 aHou, Lifang1 aIrvin, Marguerite, R1 aKooperberg, Charles1 aMinster, Ryan, L1 aMitchell, Braxton, D1 aNouraie, Mehdi1 aPsaty, Bruce, M1 aRaffield, Laura, M1 aReiner, Alexander, P1 aRich, Stephen, S1 aRotter, Jerome, I1 aShoemaker, Benjamin1 aSmith, Nicholas, L1 aTaylor, Kent, D1 aTelen, Marilyn, J1 aWeiss, Scott, T1 aZhang, Yingze1 aCosta, Nancy, Heard-1 aSun, Yan, V1 aLin, Xihong1 aCupples, Adrienne, L1 aLange, Leslie, A1 aLiu, Ching-Ti1 aLoos, Ruth, J F1 aNorth, Kari, E1 aJustice, Anne, E1 aNHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium uhttps://chs-nhlbi.org/node/9484